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  1. Detecting Out-Of-Context Objects Using Graph Contextual Reasoning Network

    Manoj Acharya, Anirban Roy, Kaushik Koneripalli, Susmit Jha, Christopher Kanan, Ajay Divakaran

  2. Cluster Attack: Query-based Adversarial Attacks on Graph with Graph-Dependent Priors

    Zhengyi Wang, Zhongkai Hao, Ziqiao Wang, Hang Su, Jun Zhu

  3. Learning Graph-based Residual Aggregation Network for Group Activity Recognition

    Wei Li, Tianzhao Yang, Xiao Wu, Zhaoquan Yuan

  4. Hypertron: Explicit Social-Temporal Hypergraph Framework for Multi-Agent Forecasting

    Yu Tian, Xingliang Huang, Ruigang Niu, Hongfeng Yu, Peijin Wang, Xian Sun

  5. Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation

    Jun Xia, Ting Wang, Jiepin Ding, Xian Wei, Mingsong Chen

  6. Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies

    Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar

  7. Hypergraph Structure Learning for Hypergraph Neural Networks

    Derun Cai, Moxian Song, Chenxi Sun, Baofeng Zhang, Shenda Hong, Hongyan Li

  8. Entity Alignment with Reliable Path Reasoning and Relation-aware Heterogeneous Graph Transformer

    Weishan Cai, Wenjun Ma, Jieyu Zhan, Yuncheng Jiang

  9. Can Abnormality be Detected by Graph Neural Networks

    Ziwei Chai, Siqi You, Yang Yang, Shiliang Pu, Jiarong Xu, Haoyang Cai, Weihao Jiang

  10. Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification

    Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng

  11. Filtration-Enhanced Graph Transformation

    Zijian Chen, Rong-Hua Li, Hongchao Qin, Huanzhong Duan, Yanxiong Lu, Qiangqiang Dai, Guoren Wang

  12. Modeling Precursors for Temporal Knowledge Graph Reasoning via Auto-encoder Structure

    Yifu Gao, Linhui Feng, Zhigang Kan, Yi Han, Linbo Qiao, Dongsheng Li

  13. Self-supervised Graph Neural Networks for Multi-behavior Recommendation

    Shuyun Gu, Xiao Wang, Chuan Shi, Ding Xiao

  14. MERIT: Learning Multi-level Representations on Temporal Graphs

    Binbin Hu, Zhengwei Wu, Jun Zhou, Ziqi Liu, Zhigang Huangfu, Zhiqiang Zhang, Chaochao Chen

  15. GraphDIVE: Graph Classification by Mixture of Diverse Experts

    Fenyu Hu, Liping Wang, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

  16. A Sparse-Motif Ensemble Graph Convolutional Network against Over-smoothing

    Xuan Jiang, Zhiyong Yang, Peisong Wen, Li Su, Qingming Huang

  17. CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning

    Di Jin, Luzhi Wang, Yizhen Zheng, Xiang Li, Fei Jiang, Wei Lin, Shirui Pan

  18. RAW-GNN: RAndom Walk Aggregation based Graph Neural Network

    Di Jin, Rui Wang, Meng Ge, Dongxiao He, Xiang Li, Wei Lin, Weixiong Zhang

  19. Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs

    Hongwei Jin, Xun Chen

  20. TGNN: A Joint Semi-supervised Framework for Graph-level Classification

    Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang

  21. TiRGN: Time-Guided Recurrent Graph Network with Local-Global Historical Patterns for Temporal Knowledge Graph Reasoning

    Yujia Li, Shiliang Sun, Jing Zhao

  22. Raising the Bar in Graph-level Anomaly Detection

    Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph

  23. Long-term Spatio-Temporal Forecasting via Dynamic Multiple-Graph Attention

    Wei Shao, Zhiling Jin, Shuo Wang, Yufan Kang, Xiao Xiao, Hamid Menouar, Zhaofeng Zhang, Junshan Zhang, Flora D. Salim

  24. Beyond Homophily: Structure-aware Path Aggregation Graph Neural Network

    Yifei Sun, Haoran Deng, Yang Yang, Chunping Wang, Jiarong Xu, Renhong Huang, Linfeng Cao, Yang Wang, Lei Chen

  25. Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion

    Zhenwei Tang, Shichao Pei, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Robert Hoehndorf, Xiangliang Zhang

  26. Augmenting Knowledge Graphs for Better Link Prediction

    Jiang Wang, Filip Ilievski, Pedro A. Szekely, Ke-Thia Yao

  27. FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs

    Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li

  28. Ensemble Multi-Relational Graph Neural Networks

    Yuling Wang, Hao Xu, Yanhua Yu, Mengdi Zhang, Zhenhao Li, Yuji Yang, Wei Wu

  29. Multi-Graph Fusion Networks for Urban Region Embedding

    Shangbin Wu, Xu Yan, Xiaoliang Fan, Shirui Pan, Shichao Zhu, Chuanpan Zheng, Ming Cheng, Cheng Wang

  30. Subgraph Neighboring Relations Infomax for Inductive Link Prediction on Knowledge Graphs

    Xiaohan Xu, Peng Zhang, Yongquan He, Chengpeng Chao, Chaoyang Yan

  31. Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting

    Hongyuan Yu, Ting Li, Weichen Yu, Jianguo Li, Yan Huang, Liang Wang, Alex X. Liu

  32. Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction

    Ruixing Zhang, Liangzhe Han, Boyi Liu, Jiayuan Zeng, Leilei Sun

  33. GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning

    Weiqi Zhang, Chen Zhang, Fugee Tsung

  34. Enhancing Sequential Recommendation with Graph Contrastive Learning

    Yixin Zhang, Yong Liu, Yonghui Xu, Hao Xiong, Chenyi Lei, Wei He, Lizhen Cui, Chunyan Miao

  35. Table2Graph: Transforming Tabular Data to Unified Weighted Graph

    Kaixiong Zhou, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu

  36. Spiking Graph Convolutional Networks

    Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo

  37. Data-Free Adversarial Knowledge Distillation for Graph Neural Networks

    Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun

  38. Proximity Enhanced Graph Neural Networks with Channel Contrast

    Wei Zhuo, Guang Tan

  39. Personalized Federated Learning With a Graph

    Fengwen Chen, Guodong Long, Zonghan Wu, Tianyi Zhou, Jing Jiang

  40. Adversarial Explanations for Knowledge Graph Embeddings

    Patrick Betz, Christian Meilicke, Heiner Stuckenschmidt

  41. Multi-view Unsupervised Graph Representation Learning

    Jiangzhang Gan, Rongyao Hu, Mengmeng Zhan, Yujie Mo, Yingying Wan, Xiaofeng Zhu

  42. Bootstrapping Informative Graph Augmentation via A Meta Learning Approach

    Hang Gao, Jiangmeng Li, Wenwen Qiang, Lingyu Si, Fuchun Sun, Changwen Zheng

  43. Attributed Graph Clustering with Dual Redundancy Reduction

    Lei Gong, Sihang Zhou, Wenxuan Tu, Xinwang Liu

  44. Learning Continuous Graph Structure with Bilevel Programming for Graph Neural Networks

    Minyang Hu, Hong Chang, Bingpeng Ma, Shiguang Shan

  45. Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs

    Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Xiaoli Li, Ru Li, Jeff Z. Pan

  46. On the Channel Pruning using Graph Convolution Network for Convolutional Neural Network Acceleration

    Di Jiang, Yuan Cao, Qiang Yang

  47. Graph Masked Autoencoder Enhanced Predictor for Neural Architecture Search

    Kun Jing, Jungang Xu, Pengfei Li

  48. DyGRAIN: An Incremental Learning Framework for Dynamic Graphs

    Seoyoon Kim, Seongjun Yun, Jaewoo Kang

  49. SGAT: Simplicial Graph Attention Network

    See Hian Lee, Feng Ji, Wee Peng Tay

  50. Rethinking the Setting of Semi-supervised Learning on Graphs

    Ziang Li, Ming Ding, Weikai Li, Zihan Wang, Ziyu Zeng, Yukuo Cen, Jie Tang

  51. Deep Graph Matching for Partial Label Learning

    Gengyu Lyu, Yanan Wu, Songhe Feng

  52. Escaping Feature Twist: A Variational Graph Auto-Encoder for Node Clustering

    Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini

  53. RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation

    Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla

  54. Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks

    Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla

  55. Initializing Then Refining: A Simple Graph Attribute Imputation Network

    Wenxuan Tu, Sihang Zhou, Xinwang Liu, Yue Liu, Zhiping Cai, En Zhu, Changwang Zhang, Jieren Cheng

  56. EMGC²F: Efficient Multi-view Graph Clustering with Comprehensive Fusion

    Danyang Wu, Jitao Lu, Feiping Nie, Rong Wang, Yuan Yuan

  57. A Simple yet Effective Method for Graph Classification

    Junran Wu, Shangzhe Li, Jianhao Li, Yicheng Pan, Ke Xu

  58. Stabilizing and Enhancing Link Prediction through Deepened Graph Auto-Encoders

    Xinxing Wu, Qiang Cheng

  59. Information Augmentation for Few-shot Node Classification

    Zongqian Wu, Peng Zhou, Guoqiu Wen, Yingying Wan, Junbo Ma, Debo Cheng, Xiaofeng Zhu

  60. Online ECG Emotion Recognition for Unknown Subjects via Hypergraph-Based Transfer Learning

    Yalan Ye, Tongjie Pan, Qianhe Meng, Jingjing Li, Li Lu

  61. Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport

    Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian

  62. Hierarchical Diffusion Scattering Graph Neural Network

    Ke Zhang, Xinyan Pu, Jiaxing Li, Jiasong Wu, Huazhong Shu, Youyong Kong

  63. RoSA: A Robust Self-Aligned Framework for Node-Node Graph Contrastive Learning

    Yun Zhu, Jianhao Guo, Fei Wu, Siliang Tang

  64. Subsequence-based Graph Routing Network for Capturing Multiple Risk Propagation Processes

    Rui Cheng, Qing Li

  65. Monolith to Microservices: Representing Application Software through Heterogeneous Graph Neural Network

    Alex Mathai, Sambaran Bandyopadhyay, Utkarsh Desai, Srikanth Tamilselvam

  66. Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction

    Jiahua Rao, Shuangjia Zheng, Sijie Mai, Yuedong Yang

  67. FOGS: First-Order Gradient Supervision with Learning-based Graph for Traffic Flow Forecasting

    Xuan Rao, Hao Wang, Liang Zhang, Jing Li, Shuo Shang, Peng Han

  68. Effective Graph Context Representation for Document-level Machine Translation

    Kehai Chen, Muyun Yang, Masao Utiyama, Eiichiro Sumita, Rui Wang, Min Zhang

  69. Interactive Information Extraction by Semantic Information Graph

    Siqi Fan, Yequan Wang, Jing Li, Zheng Zhang, Shuo Shang, Peng Han

  70. Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversation

    Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun, Yunpeng Li

  71. Neural Subgraph Explorer: Reducing Noisy Information via Target-oriented Syntax Graph Pruning

    Bowen Xing, Ivor W. Tsang

  72. Contrastive Graph Transformer Network for Personality Detection

    Yangfu Zhu, Linmei Hu, Xinkai Ge, Wanrong Peng, Bin Wu

  73. Dynamic Structure Learning through Graph Neural Network for Forecasting Soil Moisture in Precision Agriculture

    Anoushka Vyas, Sambaran Bandyopadhyay

  74. Survey on Graph Neural Network Acceleration: An Algorithmic Perspective

    Xin Liu, Mingyu Yan, Lei Deng, Guoqi Li, Xiaochun Ye, Dongrui Fan, Shirui Pan, Yuan Xie

  1. Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters

    Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc

  2. Convergence of Invariant Graph Networks

    Chen Cai, Yusu Wang

  3. Structure-Aware Transformer for Graph Representation Learning

    Dexiong Chen, Leslie O'Bray, Karsten M. Borgwardt

  4. Faster Fundamental Graph Algorithms via Learned Predictions

    Justin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang

  5. Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection

    Wenchao Chen, Long Tian, Bo Chen, Liang Dai, Zhibin Duan, Mingyuan Zhou

  6. Optimization-Induced Graph Implicit Nonlinear Diffusion

    Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

  7. From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers

    Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamás Sarlós, Adrian Weller, Thomas Weingarten

  8. PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs

    Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen

  9. SE(3) Equivariant Graph Neural Networks with Complete Local Frames

    Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu

  10. pathGCN: Learning General Graph Spatial Operators from Paths

    Moshe Eliasof, Eldad Haber, Eran Treister

  11. p-Laplacian Based Graph Neural Networks

    Guoji Fu, Peilin Zhao, Yatao Bian

  12. On the Equivalence Between Temporal and Static Equivariant Graph Representations

    Jianfei Gao, Bruno Ribeiro

  13. Large-Scale Graph Neural Architecture Search

    Chaoyu Guan, Xin Wang, Hong Chen, Ziwei Zhang, Wenwu Zhu

  14. Understanding and Improving Knowledge Graph Embedding for Entity Alignment

    Lingbing Guo, Qiang Zhang, Zequn Sun, Mingyang Chen, Wei Hu, Huajun Chen

  15. G-Mixup: Graph Data Augmentation for Graph Classification

    Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu

  16. GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks

    Yixuan He, Quan Gan, David Wipf, Gesine D. Reinert, Junchi Yan, Mihai Cucuringu

  17. Going Deeper into Permutation-Sensitive Graph Neural Networks

    Zhongyu Huang, Yingheng Wang, Chaozhuo Li, Huiguang He

  18. LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation

    David Ireland, Giovanni Montana

  19. Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations

    Jaehyeong Jo, Seul Lee, Sung Ju Hwang

  20. Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learning

    Hidetaka Kamigaito, Katsuhiko Hayashi

  21. Simultaneous Graph Signal Clustering and Graph Learning

    Abdullah Karaaslanli, Selin Aviyente

  22. DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting

    Shiyong Lan, Yitong Ma, Weikang Huang, Wenwu Wang, Hongyu Yang, Pyang Li

  23. G2CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters

    Mingjie Li, Xiaojun Guo, Yifei Wang, Yisen Wang, Zhouchen Lin

  24. Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling

    Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

  25. Let Invariant Rationale Discovery Inspire Graph Contrastive Learning

    Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua

  26. HousE: Knowledge Graph Embedding with Householder Parameterization

    Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang

  27. Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

    Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian

  28. Boosting Graph Structure Learning with Dummy Nodes

    Xin Liu, Jiayang Cheng, Yangqiu Song, Xin Jiang

  29. Local Augmentation for Graph Neural Networks

    Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu

  30. SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators

    Karolis Martinkus, Andreas Loukas, Nathanaël Perraudin, Roger Wattenhofer

  31. Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism

    Siqi Miao, Mia Liu, Pan Li

  32. SpeqNets: Sparsity-aware permutation-equivariant graph networks

    Christopher Morris, Gaurav Rattan, Sandra Kiefer, Siamak Ravanbakhsh

  33. A Theoretical Comparison of Graph Neural Network Extensions

    Pál András Papp, Roger Wattenhofer

  34. Nonlinear Feature Diffusion on Hypergraphs

    Konstantin Prokopchik, Austin R. Benson, Francesco Tudisco

  35. Graph Neural Architecture Search Under Distribution Shifts

    Yijian Qin, Xin Wang, Ziwei Zhang, Pengtao Xie, Wenwu Zhu

  36. Graph-Coupled Oscillator Networks

    T. Konstantin Rusch, Ben Chamberlain, James Rowbottom, Siddhartha Mishra, Michael M. Bronstein

  37. Rethinking Graph Neural Networks for Anomaly Detection

    Jianheng Tang, Jiajin Li, Ziqi Gao, Jia Li

  38. Cross-Space Active Learning on Graph Convolutional Networks

    Yufei Tao, Hao Wu, Shiyuan Deng

  39. What Dense Graph Do You Need for Self-Attention

    Yuxin Wang, Chu-Tak Lee, Qipeng Guo, Zhangyue Yin, Yunhua Zhou, Xuanjing Huang, Xipeng Qiu

  40. How Powerful are Spectral Graph Neural Networks

    Xiyuan Wang, Muhan Zhang

  41. Structural Entropy Guided Graph Hierarchical Pooling

    Junran Wu, Xueyuan Chen, Ke Xu, Shangzhe Li

  42. ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning

    Jun Xia, Lirong Wu, Ge Wang, Jintao Chen, Stan Z. Li

  43. Self-Supervised Representation Learning via Latent Graph Prediction

    Yaochen Xie, Zhao Xu, Shuiwang Ji

  44. Efficient Computation of Higher-Order Subgraph Attribution via Message Passing

    Ping Xiong, Thomas Schnake, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima

  45. Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning

    Ling Yang, Shenda Hong

  46. A New Perspective on the Effects of Spectrum in Graph Neural Networks

    Mingqi Yang, Yanming Shen, Rui Li, Heng Qi, Qiang Zhang, Baocai Yin

  47. Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks

    Zhaoning Yu, Hongyang Gao

  48. GraphFM: Improving Large-Scale GNN Training via Feature Momentum

    Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji

  49. Deep and Flexible Graph Neural Architecture Search

    Wentao Zhang, Zheyu Lin, Yu Shen, Yang Li, Zhi Yang, Bin Cui

  50. NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning

    Wentao Zhang, Zeang Sheng, Mingyu Yang, Yang Li, Yu Shen, Zhi Yang, Bin Cui

  51. Learning to Solve PDE-constrained Inverse Problems with Graph Networks

    Qingqing Zhao, David B. Lindell, Gordon Wetzstein

  52. Neural-Symbolic Models for Logical Queries on Knowledge Graphs

    Zhaocheng Zhu, Mikhail Galkin, Zuobai Zhang, Jian Tang

  1. Motif Prediction with Graph Neural Networks

    Maciej Besta, Raphael Grob, Cesare Miglioli, Nicola Bernold, Grzegorz Kwasniewski, Gabriel Gjini, Raghavendra Kanakagiri, Saleh Ashkboos, Lukas Gianinazzi, Nikoli Dryden, Torsten Hoefler

  2. Efficient Join Order Selection Learning with Graph-based Representation

    Jin Chen, Guanyu Ye, Yan Zhao, Shuncheng Liu, Liwei Deng, Xu Chen, Rui Zhou, Kai Zheng

  3. Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation

    Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King

  4. On Structural Explanation of Bias in Graph Neural Networks

    Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li

  5. FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks

    Kaituo Feng, Changsheng Li, Ye Yuan, Guoren Wang

  6. Meta-Learned Metrics over Multi-Evolution Temporal Graphs

    Dongqi Fu, Liri Fang, Ross Maciejewski, Vetle I. Torvik, Jingrui He

  7. Subset Node Anomaly Tracking over Large Dynamic Graphs

    Xingzhi Guo, Baojian Zhou, Steven Skiena

  8. Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction

    Liangzhe Han, Xiaojian Ma, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv, Hui Xiong

  9. Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation

    Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu

  10. GraphMAE: Self-Supervised Masked Graph Autoencoders

    Zhenyu Hou, Xiao Liu, Yukuo Cen, Yuxiao Dong, Hongxia Yang, Chunjie Wang, Jie Tang

  11. Global Self-Attention as a Replacement for Graph Convolution

    Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian

  12. Dual-Geometric Space Embedding Model for Two-View Knowledge Graphs

    Roshni G. Iyer, Yunsheng Bai, Wei Wang, Yizhou Sun

  13. Detecting Cash-out Users via Dense Subgraphs

    Yingsheng Ji, Zheng Zhang, Xinlei Tang, Jiachen Shen, Xi Zhang, Guangwen Yang

  14. A Spectral Representation of Networks: The Path of Subgraphs

    Shengmin Jin, Hao Tian, Jiayu Li, Reza Zafarani

  15. Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective

    Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang

  16. Condensing Graphs via One-Step Gradient Matching

    Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin

  17. JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks

    Jian Kang, Qinghai Zhou, Hanghang Tong

  18. CoRGi: Content-Rich Graph Neural Networks with Attention

    Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zhang, Miltiadis Allamanis

  19. FlowGEN: A Generative Model for Flow Graphs

    Furkan Kocayusufoglu, Arlei Silva, Ambuj K. Singh

  20. Variational Inference for Training Graph Neural Networks in Low-Data Regime through Joint Structure-Label Estimation

    Danning Lao, Xinyu Yang, Qitian Wu, Junchi Yan

  21. KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction

    Han Li, Dan Zhao, Jianyang Zeng

  22. Domain Adaptation in Physical Systems via Graph Kernel

    Haoran Li, Hanghang Tong, Yang Weng

  23. Mining Spatio-Temporal Relations via Self-Paced Graph Contrastive Learning

    Rongfan Li, Ting Zhong, Xinke Jiang, Goce Trajcevski, Jin Wu, Fan Zhou

  24. Graph Structural Attack by Perturbing Spectral Distance

    Lu Lin, Ethan Blaser, Hongning Wang

  25. Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems

    Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao

  26. User-Event Graph Embedding Learning for Context-Aware Recommendation

    Dugang Liu, Mingkai He, Jinwei Luo, Jiangxu Lin, Meng Wang, Xiaolian Zhang, Weike Pan, Zhong Ming

  27. Graph-in-Graph Network for Automatic Gene Ontology Description Generation

    Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Adelaide Woicik, Sheng Wang

  28. Joint Knowledge Graph Completion and Question Answering

    Lihui Liu, Boxin Du, Jiejun Xu, Yinglong Xia, Hanghang Tong

  29. RL2: A Call for Simultaneous Representation Learning and Rule Learning for Graph Streams

    Qu Liu, Tingjian Ge

  30. Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries

    Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang

  31. UD-GNN: Uncertainty-aware Debiased Training on Semi-Homophilous Graphs

    Yang Liu, Xiang Ao, Fuli Feng, Qing He

  32. Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation

    Bin Lu, Xiaoying Gan, Lina Yang, Weinan Zhang, Luoyi Fu, Xinbing Wang

  33. Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer

    Bin Lu, Xiaoying Gan, Weinan Zhang, Huaxiu Yao, Luoyi Fu, Xinbing Wang

  34. Learning Causal Effects on Hypergraphs

    Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, Jaime Teevan

  35. Evaluating Knowledge Graph Accuracy Powered by Optimized Human-machine Collaboration

    Yifan Qi, Weiguo Zheng, Liang Hong, Lei Zou

  36. Rep2Vec: Repository Embedding via Heterogeneous Graph Adversarial Contrastive Learning

    Yiyue Qian, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang

  37. Graph-Flashback Network for Next Location Recommendation

    Xuan Rao, Lisi Chen, Yong Liu, Shuo Shang, Bin Yao, Peng Han

  38. SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs

    Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans

  39. Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

    Zezhi Shao, Zhao Zhang, Fei Wang, Yongjun Xu

  40. GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks

    Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li

  41. Learning on Graphs with Out-of-Distribution Nodes

    Yu Song, Donglin Wang

  42. Towards an Optimal Asymmetric Graph Structure for Robust Semi-supervised Node Classification

    Zixing Song, Yifei Zhang, Irwin King

  43. Causal Attention for Interpretable and Generalizable Graph Classification

    Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua

  44. GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks

    Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, Xin Wang

  45. Streaming Graph Neural Networks with Generative Replay

    Junshan Wang, Wenhao Zhu, Guojie Song, Liang Wang

  46. Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage

    Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr

  47. Graph Neural Networks with Node-wise Architecture

    Zhen Wang, Zhewei Wei, Yaliang Li, Weirui Kuang, Bolin Ding

  48. Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction

    Qianlong Wen, Zhongyu Ouyang, Jianfei Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang

  49. Robust Tensor Graph Convolutional Networks via T-SVD based Graph Augmentation

    Zhebin Wu, Lin Shu, Ziyue Xu, Yaomin Chang, Chuan Chen, Zibin Zheng

  50. Self-Supervised Hypergraph Transformer for Recommender Systems

    Lianghao Xia, Chao Huang, Chuxu Zhang

  51. Ultrahyperbolic Knowledge Graph Embeddings

    Bo Xiong, Shichao Zhu, Mojtaba Nayyeri, Chengjin Xu, Shirui Pan, Chuan Zhou, Steffen Staab

  52. Towards a Native Quantum Paradigm for Graph Representation Learning: A Sampling-based Recurrent Embedding Approach

    Ge Yan, Yehui Tang, Junchi Yan

  53. Enhancing Machine Learning Approaches for Graph Optimization Problems with Diversifying Graph Augmentation

    Chen-Hsu Yang, Chih-Ya Shen

  54. Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation

    Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li

  55. TrajGAT: A Graph-based Long-term Dependency Modeling Approach for Trajectory Similarity Computation

    Di Yao, Haonan Hu, Lun Du, Gao Cong, Shi Han, Jingping Bi

  56. Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting

    Junchen Ye, Zihan Liu, Bowen Du, Leilei Sun, Weimiao Li, Yanjie Fu, Hui Xiong

  57. Accurate Node Feature Estimation with Structured Variational Graph Autoencoder

    Jaemin Yoo, Hyunsik Jeon, Jinhong Jung, U Kang

  58. ROLAND: Graph Learning Framework for Dynamic Graphs

    Jiaxuan You, Tianyu Du, Jure Leskovec

  59. Multiplex Heterogeneous Graph Convolutional Network

    Pengyang Yu, Chaofan Fu, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong

  60. Dual Bidirectional Graph Convolutional Networks for Zero-shot Node Classification

    Qin Yue, Jiye Liang, Junbiao Cui, Liang Bai

  61. Variational Graph Author Topic Modeling

    Delvin Ce Zhang, Hady Wirawan Lauw

  62. Few-shot Heterogeneous Graph Learning via Cross-domain Knowledge Transfer

    Qiannan Zhang, Xiaodong Wu, Qiang Yang, Chuxu Zhang, Xiangliang Zhang

  63. Model Degradation Hinders Deep Graph Neural Networks

    Wentao Zhang, Zeang Sheng, Ziqi Yin, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui

  64. Improving Social Network Embedding via New Second-Order Continuous Graph Neural Networks

    Yanfu Zhang, Shangqian Gao, Jian Pei, Heng Huang

  65. COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning

    Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King

  66. Instant Graph Neural Networks for Dynamic Graphs

    Yanping Zheng, Hanzhi Wang, Zhewei Wei, Jiajun Liu, Sibo Wang

  67. How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications

    Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra

  68. Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding

    Mohammad Amini, Zhanguang Zhang, Surya Penmetsa, Yingxue Zhang, Jianye Hao, Wulong Liu

  69. Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks

    Wendong Bi, Bingbing Xu, Xiaoqian Sun, Zidong Wang, Huawei Shen, Xueqi Cheng

  70. BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning

    Junru Chen, Yang Yang, Tao Yu, Yingying Fan, Xiaolong Mo, Carl Yang

  71. Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks

    Shengyu Chen, Jacob A. Zwart, Xiaowei Jia

  72. AntiBenford Subgraphs: Unsupervised Anomaly Detection in Financial Networks

    Tianyi Chen, Charalampos E. Tsourakakis

  73. Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning

    Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong

  74. Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning

    Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong

  75. Learning Sparse Latent Graph Representations for Anomaly Detection in Multivariate Time Series

    Siho Han, Simon S. Woo

  76. ERNIE-GeoL: A Geography-and-Language Pre-trained Model and its Applications in Baidu Maps

    Jizhou Huang, Haifeng Wang, Yibo Sun, Yunsheng Shi, Zhengjie Huang, An Zhuo, Shikun Feng

  77. Graph Neural Network Training and Data Tiering

    Seungwon Min, Kun Wu, Mert Hidayetoglu, Jinjun Xiong, Xiang Song, Wen-Mei Hwu

  78. GraphWorld: Fake Graphs Bring Real Insights for GNNs

    John Palowitch, Anton Tsitsulin, Brandon Mayer, Bryan Perozzi

  79. Improving Relevance Modeling via Heterogeneous Behavior Graph Learning in Bing Ads

    Bochen Pang, Chaozhuo Li, Yuming Liu, Jianxun Lian, Jianan Zhao, Hao Sun, Weiwei Deng, Xing Xie, Qi Zhang

  80. Friend Recommendations with Self-Rescaling Graph Neural Networks

    Xiran Song, Jianxun Lian, Hong Huang, Mingqi Wu, Hai Jin, Xing Xie

  81. A Graph Learning Based Framework for Billion-Scale Offline User Identification

    Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou

  82. FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning

    Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou

  83. Connecting the Hosts: Street-Level IP Geolocation with Graph Neural Networks

    Zhiyuan Wang, Fan Zhou, Wenxuan Zeng, Goce Trajcevski, Chunjing Xiao, Yong Wang, Kai Chen

  84. Graph2Route: A Dynamic Spatial-Temporal Graph Neural Network for Pick-up and Delivery Route Prediction

    Haomin Wen, Youfang Lin, Xiaowei Mao, Fan Wu, Yiji Zhao, Haochen Wang, Jianbin Zheng, Lixia Wu, Haoyuan Hu, Huaiyu Wan

  85. Graph Neural Networks for Multimodal Single-Cell Data Integration

    Hongzhi Wen, Jiayuan Ding, Wei Jin, Yiqi Wang, Yuying Xie, Jiliang Tang

  86. Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator

    Tailin Wu, Qinchen Wang, Yinan Zhang, Rex Ying, Kaidi Cao, Rok Sosic, Ridwan Jalali, Hassan Hamam, Marko Maucec, Jure Leskovec

  87. Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph

    Chin-Chia Michael Yeh, Mengting Gu, Yan Zheng, Huiyuan Chen, Javid Ebrahimi, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang

  88. Graph Attention Multi-Layer Perceptron

    Wentao Zhang, Ziqi Yin, Zeang Sheng, Yang Li, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui

  89. Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs

    Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, George Karypis

  90. Dynamic Graph Segmentation for Deep Graph Neural Networks

    Johan Kok Zhi Kang, Suwei Yang, Suriya Venkatesan, Sien Yi Tan, Feng Cheng, Bingsheng He

  91. Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks

    Dingyi Zhuang, Shenhao Wang, Haris N. Koutsopoulos, Jinhua Zhao

  1. Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering

    Minghao Zhao, Le Wu, Yile Liang, Lei Chen, Jian Zhang, Qilin Deng, Kai Wang, Xudong Shen, Tangjie Lv, Runze Wu

  2. Hypergraph Contrastive Collaborative Filtering

    Lianghao Xia, Chao Huang, Yong Xu, Jiashu Zhao, Dawei Yin, Jimmy X. Huang

  3. Graph Trend Filtering Networks for Recommendation

    Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li

  4. Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering

    Changxin Tian, Yuexiang Xie, Yaliang Li, Nan Yang, Wayne Xin Zhao

  5. Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer

    Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Da Luo, Kangyi Lin, Junzhou Huang, Sophia Ananiadou, Peilin Zhao

  6. DAWAR: Diversity-aware Web APIs Recommendation for Mashup Creation based on Correlation Graph

    Wenwen Gong, Xuyun Zhang, Yifei Chen, Qiang He, Amin Beheshti, Xiaolong Xu, Chao Yan, Lianyong Qi

  7. Introducing Problem Schema with Hierarchical Exercise Graph for Knowledge Tracing

    Hanshuang Tong, Zhen Wang, Yun Zhou, Shiwei Tong, Wenyuan Han, Qi Liu

  8. Few-shot Node Classification on Attributed Networks with Graph Meta-learning

    Yonghao Liu, Mengyu Li, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng, Renchu Guan

  9. Personalized Fashion Compatibility Modeling via Metapath-guided Heterogeneous Graph Learning

    Weili Guan, Fangkai Jiao, Xuemeng Song, Haokun Wen, Chung-Hsing Yeh, Xiaojun Chang

  10. KETCH: Knowledge Graph Enhanced Thread Recommendation in Healthcare Forums

    Limeng Cui, Dongwon Lee

  11. Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations

    Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, Mirko Marras

  12. Co-clustering Interactions via Attentive Hypergraph Neural Network

    Tianchi Yang, Cheng Yang, Luhao Zhang, Chuan Shi, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang

  13. Incorporating Context Graph with Logical Reasoning for Inductive Relation Prediction

    Qika Lin, Jun Liu, Fangzhi Xu, Yudai Pan, Yifan Zhu, Lingling Zhang, Tianzhe Zhao

  14. Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion

    Xiang Chen, Ningyu Zhang, Lei Li, Shumin Deng, Chuanqi Tan, Changliang Xu, Fei Huang, Luo Si, Huajun Chen

  15. Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective

    Ying Zhou, Xuanang Chen, Ben He, Zheng Ye, Le Sun

  16. Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding

    Mingyang Chen, Wen Zhang, Yushan Zhu, Hongting Zhou, Zonggang Yuan, Changliang Xu, Huajun Chen

  17. Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning

    Fangzhi Xu, Jun Liu, Qika Lin, Yudai Pan, Lingling Zhang

  18. Hierarchical Multi-Task Graph Recurrent Network for Next POI Recommendation

    Nicholas Lim, Bryan Hooi, See-Kiong Ng, Yong Liang Goh, Renrong Weng, Rui Tan

  19. Learning Graph-based Disentangled Representations for Next POI Recommendation

    Zhaobo Wang, Yanmin Zhu, Haobing Liu, Chunyang Wang

  20. Less is More: Reweighting Important Spectral Graph Features for Recommendation

    Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine

  21. A Review-aware Graph Contrastive Learning Framework for Recommendation

    Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li

  22. Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation

    Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Lizhen Cui, Quoc Viet Hung Nguyen

  23. Knowledge Graph Contrastive Learning for Recommendation

    Yuhao Yang, Chao Huang, Lianghao Xia, Chenliang Li

  24. Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification

    Kai Zhang, Qi Liu, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen

  25. An Attribute-Driven Mirror Graph Network for Session-based Recommendation

    Siqi Lai, Erli Meng, Fan Zhang, Chenliang Li, Bin Wang, Aixin Sun

  26. AutoGSR: Neural Architecture Search for Graph-based Session Recommendation

    Jingfan Chen, Guanghui Zhu, Haojun Hou, Chunfeng Yuan, Yihua Huang

  27. Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders

    Jinning Li, Huajie Shao, Dachun Sun, Ruijie Wang, Yuchen Yan, Jinyang Li, Shengzhong Liu, Hanghang Tong, Tarek F. Abdelzaher

  28. Multi-modal Graph Contrastive Learning for Micro-video Recommendation

    Zixuan Yi, Xi Wang, Iadh Ounis, Craig MacDonald

  29. Adversarial Graph Perturbations for Recommendations at Scale

    Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Xia Hu, Fei Wang, Hao Yang

  30. Graph Capsule Network with a Dual Adaptive Mechanism

    Xiangping Zheng, Xun Liang, Bo Wu, Yuhui Guo, Xuan Zhang

  31. Enhancing Hypergraph Neural Networks with Intent Disentanglement for Session-based Recommendation

    Yinfeng Li, Chen Gao, Hengliang Luo, Depeng Jin, Yong Li

  32. Distilling Knowledge on Text Graph for Social Media Attribute Inference

    Quan Li, Xiaoting Li, Lingwei Chen, Dinghao Wu

  33. DH-HGCN: Dual Homogeneity Hypergraph Convolutional Network for Multiple Social Recommendations

    Jiadi Han, Qian Tao, Yufei Tang, Yuhan Xia

  34. GraFN: Semi-Supervised Node Classification on Graph with Few Labels via Non-Parametric Distribution Assignment

    Junseok Lee, Yunhak Oh, Yeonjun In, Namkyeong Lee, Dongmin Hyun, Chanyoung Park

  35. GraphAD: A Graph Neural Network for Entity-Wise Multivariate Time-Series Anomaly Detection

    Xu Chen, Qiu Qiu, Changshan Li, Kunqing Xie

  36. DisenCTR: Dynamic Graph-based Disentangled Representation for Click-Through Rate Prediction

    Yifan Wang, Yifang Qin, Fang Sun, Bo Zhang, Xuyang Hou, Ke Hu, Jia Cheng, Jun Lei, Ming Zhang

  37. An MLP-based Algorithm for Efficient Contrastive Graph Recommendations

    Siwei Liu, Iadh Ounis, Craig Macdonald

  38. Assessing Scientific Research Papers with Knowledge Graphs

    Kexuan Sun, Zhiqiang Qiu, Abel Salinas, Yuzhong Huang, Dong-Ho Lee, Daniel Benjamin, Fred Morstatter, Xiang Ren, Kristina Lerman, Jay Pujara

  39. MuchSUM: Multi-channel Graph Neural Network for Extractive Summarization

    Qianren Mao, Hongdong Zhu, Junnan Liu, Cheng Ji, Hao Peng, Jianxin Li, Lihong Wang, Zheng Wang

  40. LightSGCN: Powering Signed Graph Convolution Network for Link Sign Prediction with Simplified Architecture Design

    Haoxin Liu

  41. Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network

    Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi

  1. Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.

    Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang

  2. Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNs.

    Seiji Maekawa, Koki Noda, Yuya Sasaki, Makoto Onizuka

  3. Vision GNN: An Image is Worth Graph of Nodes.

    Kai Han, Yunhe Wang, Jianyuan Guo, Yehui Tang, Enhua Wu

  4. Does GNN Pretraining Help Molecular Representation?

    Ruoxi Sun, Hanjun Dai, Adams Wei Yu

  5. ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective.

    Yihong Chen, Pushkar Mishra, Luca Franceschi, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel

  6. Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs.

    Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Lió, Michael M. Bronstein

  7. OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs.

    Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro

  8. MGNNI: Multiscale Graph Neural Networks with Implicit Layers.

    Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao

  9. NeuroSchedule: A Novel Effective GNN-based Scheduling Method for High-level Synthesis.

    Jun Zeng, Mingyang Kou, Hailong Yao

  10. Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding.

    Ruipeng Zhang, Chenning Yu, Jingkai Chen, Chuchu Fan, Sicun Gao

  11. Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.

    Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron

  12. A Practical, Progressively-Expressive GNN.

    Lingxiao Zhao, Neil Shah, Leman Akoglu

  13. PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery.

    Yasmin Salehi, Dennis Giannacopoulos

  14. NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search.

    Yijian Qin, Ziwei Zhang, Xin Wang, Zeyang Zhang, Wenwu Zhu

  15. Decoupled Self-supervised Learning for Graphs.

    Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang

  16. ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs.

    Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji

  17. Revisiting Heterophily For Graph Neural Networks.

    Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup

  18. Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats.

    Hongwei Jin, Zishun Yu, Xinhua Zhang

  19. Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative.

    Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang

  20. GOOD: A Graph Out-of-Distribution Benchmark.

    Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji

  21. Not too little, not too much: a theoretical analysis of graph (over)smoothing.

    Nicolas Keriven

  22. Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks.

    Ching-Yao Chuang, Stefanie Jegelka

  23. Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum.

    Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei

  24. S3GC: Scalable Self-Supervised Graph Clustering.

    Fnu Devvrit, Aditya Sinha, Inderjit S. Dhillon, Prateek Jain

  25. Pseudo-Riemannian Graph Convolutional Networks.

    Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou, Steffen Staab

  26. Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems.

    Abishek Thangamuthu, Gunjan Kumar, Suresh Bishnoi, Ravinder Bhattoo, N. M. Anoop Krishnan, Sayan Ranu

  27. Graph Convolution Network based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy.

    Leyan Deng, Defu Lian, Chenwang Wu, Enhong Chen

  28. Redundancy-Free Message Passing for Graph Neural Networks.

    Rongqin Chen, Shenghui Zhang, Leong Hou U, Ye Li

  29. Association Graph Learning for Multi-Task Classification with Category Shifts.

    Jiayi Shen, Zehao Xiao, Xiantong Zhen, Cees Snoek, Marcel Worring

  30. EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks.

    Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei

  31. How Powerful are K-hop Message Passing Graph Neural Networks.

    Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang

  32. Generalization Analysis of Message Passing Neural Networks on Large Random Graphs.

    Sohir Maskey, Ron Levie, Yunseok Lee, Gitta Kutyniok

  33. Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture.

    Libin Zhu, Chaoyue Liu, Misha Belkin

  34. A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking.

    Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang

  35. Geodesic Graph Neural Network for Efficient Graph Representation Learning.

    Lecheng Kong, Yixin Chen, Muhan Zhang

  36. High-Order Pooling for Graph Neural Networks with Tensor Decomposition.

    Chenqing Hua, Guillaume Rabusseau, Jian Tang

  37. Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift.

    Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Zhou Qin, Wenwu Zhu

  38. GraphQNTK: Quantum Neural Tangent Kernel for Graph Data.

    Yehui Tang, Junchi Yan

  39. On the Robustness of Graph Neural Diffusion to Topology Perturbations.

    Yang Song, Qiyu Kang, Sijie Wang, Kai Zhao, Wee Peng Tay

  40. Few-shot Relational Reasoning via Connection Subgraph Pretraining.

    Qian Huang, Hongyu Ren, Jure Leskovec

  41. Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited.

    Mingguo He, Zhewei Wei, Ji-Rong Wen

  42. Evaluating Graph Generative Models with Contrastively Learned Features.

    Hamed Shirzad, Kaveh Hassani, Danica J. Sutherland

  43. An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries.

    Aryan Pedawi, Pawel Gniewek, Chaoyi Chang, Brandon M. Anderson, Henry van den Bedem

  44. Are Defenses for Graph Neural Networks Robust?

    Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski

  45. Equivariant Graph Hierarchy-Based Neural Networks.

    Jiaqi Han, Wenbing Huang, Tingyang Xu, Yu Rong

  46. Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination.

    Yizhen Zheng, Shirui Pan, Vincent C. S. Lee, Yu Zheng, Philip S. Yu

  47. Template based Graph Neural Network with Optimal Transport Distances.

    Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty

  48. Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks.

    Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li

  49. Learning Invariant Graph Representations for Out-of-Distribution Generalization.

    Haoyang Li, Ziwei Zhang, Xin Wang, Wenwu Zhu

  50. Task-Agnostic Graph Explanations.

    Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward W. Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji

  51. A Variational Edge Partition Model for Supervised Graph Representation Learning.

    Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou

  52. CGLB: Benchmark Tasks for Continual Graph Learning.

    Xikun Zhang, Dongjin Song, Dacheng Tao

  53. What Makes Graph Neural Networks Miscalibrated?

    Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers

  54. Analyzing Data-Centric Properties for Graph Contrastive Learning.

    Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan

  55. Learning Bipartite Graphs: Heavy Tails and Multiple Components.

    José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel P. Palomar

  56. Graph Self-supervised Learning with Accurate Discrepancy Learning.

    Dongki Kim, Jinheon Baek, Sung Ju Hwang

  57. Recipe for a General, Powerful, Scalable Graph Transformer.

    Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini

  58. Pure Transformers are Powerful Graph Learners.

    Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong

  59. Periodic Graph Transformers for Crystal Material Property Prediction.

    Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji

  60. Co-Modality Graph Contrastive Learning for Imbalanced Node Classification.

    Yiyue Qian, Chunhui Zhang, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang

  61. Learning NP-Hard Multi-Agent Assignment Planning using GNN: Inference on a Random Graph and Provable Auction-Fitted Q-learning.

    Hyunwook Kang, Taehwan Kwon, Jinkyoo Park, James R. Morrison

  62. Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs.

    Ruijie Wang, Zheng Li, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek F. Abdelzaher

  63. Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering.

    Yaming Yang, Ziyu Guan, Zhe Wang, Wei Zhao, Cai Xu, Weigang Lu, Jianbin Huang

  64. Neural Topological Ordering for Computation Graphs.

    Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague, Wonseok Jeon, Roberto Bondesan, Herke van Hoof, Christopher Lott, Weiliang Will Zeng, Piero Zappi

  65. Graph Learning Assisted Multi-Objective Integer Programming.

    Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Abhishek Gupta, Mingyan Lin

  66. Exact Shape Correspondence via 2D graph convolution.

    Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Kaili Ma, Bo Han, Bo Li, James Cheng

  67. SHINE: SubHypergraph Inductive Neural nEtwork.

    Yuan Luo

  68. Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks.

    Yijing Liu, Qinxian Liu, Jian-Wei Zhang, Haozhe Feng, Zhongwei Wang, Zihan Zhou, Wei Chen

  69. Graph Neural Networks with Adaptive Readouts.

    David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò

  70. GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games.

    Shichang Zhang, Yozen Liu, Neil Shah, Yizhou Sun

  71. Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs.

    Ming Jin, Yuan-Fang Li, Shirui Pan

  72. OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs.

    Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro

  73. Versatile Multi-stage Graph Neural Network for Circuit Representation.

    Shuwen Yang, Zhihao Yang, Dong Li, Yingxue Zhang, Zhanguang Zhang, Guojie Song, Jianye Hao

  74. Contrastive Graph Structure Learning via Information Bottleneck for Recommendation.

    Chunyu Wei, Jian Liang, Di Liu, Fei Wang

  75. Graph Neural Networks are Dynamic Programmers.

    Andrew Joseph Dudzik, Petar Velickovic

  76. Ordered Subgraph Aggregation Networks.

    Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, Christopher Morris

  77. Hierarchical Graph Transformer with Adaptive Node Sampling.

    Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee

  78. MGNNI: Multiscale Graph Neural Networks with Implicit Layers.

    Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao

  79. Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs.

    Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng

  80. Long Range Graph Benchmark.

    Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini

  81. GREED: A Neural Framework for Learning Graph Distance Functions.

    Rishabh Ranjan, Siddharth Grover, Sourav Medya, Venkatesan T. Chakaravarthy, Yogish Sabharwal, Sayan Ranu

  82. Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank.

    Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong

  83. DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection.

    Xuanwen Huang, Yang Yang, Yang Wang, Chunping Wang, Zhisheng Zhang, Jiarong Xu, Lei Chen, Michalis Vazirgiannis

  84. Contrastive Language-Image Pre-Training with Knowledge Graphs.

    Xuran Pan, Tianzhu Ye, Dongchen Han, Shiji Song, Gao Huang

  85. Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions.

    Masanobu Horie, Naoto Mitsume

  86. Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection.

    Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal

  87. Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure.

    Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang

  88. Non-Linear Coordination Graphs.

    Yipeng Kang, Tonghan Wang, Qianlan Yang, Xiaoran Wu, Chongjie Zhang

  89. CLEAR: Generative Counterfactual Explanations on Graphs.

    Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li

  90. Learning Physical Dynamics with Subequivariant Graph Neural Networks.

    Jiaqi Han, Wenbing Huang, Hengbo Ma, Jiachen Li, Josh Tenenbaum, Chuang Gan

  91. BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.

    Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu

  92. Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks.

    Arian R. Jamasb, Ramón Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lió, Tom L. Blundell

  93. Simplified Graph Convolution with Heterophily.

    Sudhanshu Chanpuriya, Cameron Musco

  94. Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks.

    Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner

  95. Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks.

    Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi

  96. NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification.

    Qitian Wu, Wentao Zhao, Zenan Li, David P. Wipf, Junchi Yan

  97. Parameter-free Dynamic Graph Embedding for Link Prediction.

    Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Ning Gu

  98. Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias.

    Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li

  99. Label-invariant Augmentation for Semi-Supervised Graph Classification.

    Han Yue, Chunhui Zhang, Chuxu Zhang, Hongfu Liu

  100. Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks.

    Chenxiao Yang, Qitian Wu, Junchi Yan

  101. Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network.

    Ravinder Bhattoo, Sayan Ranu, N. M. Anoop Krishnan

  102. GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs.

    Zenan Li, Qitian Wu, Fan Nie, Junchi Yan

  103. Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders.

    Kiarash Zahirnia, Oliver Schulte, Parmis Nadaf, Ke Li

  104. Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries.

    Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron

  105. Symmetry-induced Disentanglement on Graphs.

    Giangiacomo Mercatali, André Freitas, Vikas Garg

  106. SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks.

    Davide Buffelli, Pietro Lió, Fabio Vandin

  107. Learning to Compare Nodes in Branch and Bound with Graph Neural Networks.

    Abdel Ghani Labassi, Didier Chételat, Andrea Lodi

  108. Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations.

    Ivan Marisca, Andrea Cini, Cesare Alippi

  109. Robust Graph Structure Learning via Multiple Statistical Tests.

    Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin

  110. Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks.

    Indradyumna Roy, Soumen Chakrabarti, Abir De

  111. Provably expressive temporal graph networks.

    Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg

  112. Uncovering the Structural Fairness in Graph Contrastive Learning.

    Ruijia Wang, Xiao Wang, Chuan Shi, Le Song

  113. On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs.

    Arjun Subramonian, Kai-Wei Chang, Yizhou Sun

  114. Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks.

    Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann

  115. Neural Approximation of Graph Topological Features.

    Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen

  116. Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective.

    Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li

  117. Graph Neural Network Bandits.

    Parnian Kassraie, Andreas Krause, Ilija Bogunovic

  118. Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains.

    Kiarash Shamsi, Friedhelm Victor, Murat Kantarcioglu, Yulia R. Gel, Cuneyt Gurcan Akcora

  119. TwiBot-22: Towards Graph-Based Twitter Bot Detection.

    Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo

  120. Deep Generative Model for Periodic Graphs.

    Shiyu Wang, Xiaojie Guo, Liang Zhao

  121. PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery.

    Yasmin Salehi, Dennis Giannacopoulos

  122. Deep Bidirectional Language-Knowledge Graph Pretraining.

    Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D. Manning, Percy Liang, Jure Leskovec

  123. CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference.

    Ran Ran, Wei Wang, Quan Gang, Jieming Yin, Nuo Xu, Wujie Wen

  124. Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks

    Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf

  125. Graph Reordering for Cache-Efficient Near Neighbor Search.

    Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava

  126. Graph Few-shot Learning with Task-specific Structures.

    Song Wang, Chen Chen, Jundong Li

  127. OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport.

    Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang

  1. KRAF: A Flexible Advertising Framework using Knowledge Graph-Enriched Multi-Agent Reinforcement Learning.

    Jose A. Ayala-Romero, Péter Mernyei, Bichen Shi, Diego Mazón

  2. Memory Graph with Message Rehearsal for Multi-Turn Dialogue Generation.

    Xiaoyu Cai, Yao Fu, Hong Zhao, Weihao Jiang, Shiliang Pu

  3. Towards Self-supervised Learning on Graphs with Heterophily.

    Jingfan Chen, Guanghui Zhu, Yifan Qi, Chunfeng Yuan, Yihua Huang

  4. GCF-RD: A Graph-based Contrastive Framework for Semi-Supervised Learning on Relational Databases.

    Runjin Chen, Tong Li, Yanyan Shen, Luyu Qiu, Kaidi Li, Caleb Chen Cao

  5. Explainable Link Prediction in Knowledge Hypergraphs.

    Zirui Chen, Xin Wang, Chenxu Wang, Jianxin Li

  6. Finding Heterophilic Neighbors via Confidence-based Subgraph Matching for Semi-supervised Node Classification.

    Yoonhyuk Choi, Jiho Choi, Taewook Ko, Hyungho Byun, Chong-Kwon Kim

  7. Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entities.

    Yuanning Cui, Yuxin Wang, Zequn Sun, Wenqiang Liu, Yiqiao Jiang, Kexin Han, Wei Hu

  8. Higher-order Clustering and Pooling for Graph Neural Networks.

    Alexandre Duval, Fragkiskos D. Malliaros

  9. MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio.

    Jinjia Feng, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei, Hongteng Xu

  10. GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search.

    Xinshun Feng, Herun Wan, Shangbin Feng, Hongrui Wang, Qinghua Zheng, Jun Zhou, Minnan Luo

  11. Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction.

    Hao Geng, Deqing Wang, Fuzhen Zhuang, Xuehua Ming, Chenguang Du, Ting Jiang, Haolong Guo, Rui Liu

  12. ITSM-GCN: Informative Training Sample Mining for Graph Convolutional Network-based Collaborative Filtering.

    Kaiqi Gong, Xiao Song, Senzhang Wang, Songsong Liu, Yong Li

  13. Evolutionary Preference Learning via Graph Nested GRU ODE for Session-based Recommendation.

    Jiayan Guo, Peiyan Zhang, Chaozhuo Li, Xing Xie, Yan Zhang, Sunghun Kim

  14. Multi-Aggregator Time-Warping Heterogeneous Graph Neural Network for Personalized Micro-Video Recommendation.

    Jinkun Han, Wei Li, Zhipeng Cai, Yingshu Li

  15. Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs.

    Phillip Howard, Arden Ma, Vasudev Lal, Ana Paula Simões, Daniel Korat, Oren Pereg, Moshe Wasserblat, Gadi Singer

  16. Discovering Fine-Grained Semantics in Knowledge Graph Relations.

    Nitisha Jain, Ralf Krestel

  17. Extracting Drug-drug Interactions from Biomedical Texts using Knowledge Graph Embeddings and Multi-focal Loss.

    Xin Jin, Xia Sun, Jiacheng Chen, Richard F. E. Sutcliffe

  18. X-GOAL: Multiplex Heterogeneous Graph Prototypical Contrastive Learning.

    Baoyu Jing, Shengyu Feng, Yuejia Xiang, Xi Chen, Yu Chen, Hanghang Tong

  19. Contrastive Representation Learning for Conversational Question Answering over Knowledge Graphs.

    Endri Kacupaj, Kuldeep Singh, Maria Maleshkova, Jens Lehmann

  20. SWAG-Net: Semantic Word-Aware Graph Network for Temporal Video Grounding.

    Sunoh Kim, Taegil Ha, Kimin Yun, Jin Young Choi

  21. Relational Self-Supervised Learning on Graphs.

    Namkyeong Lee, Dongmin Hyun, Junseok Lee, Chanyoung Park

  22. Automated Spatio-Temporal Synchronous Modeling with Multiple Graphs for Traffic Prediction.

    Fuxian Li, Huan Yan, Guangyin Jin, Yue Liu, Yong Li, Depeng Jin

  23. MDGCF: Multi-Dependency Graph Collaborative Filtering with Neighborhood- and Homogeneous-level Dependencies.

    Guohui Li, Zhiqiang Guo, Jianjun Li, Chaoyang Wang

  24. Heterogeneous Graph Attention Network for Drug-Target Interaction Prediction.

    Mei Li, Xiangrui Cai, Linyu Li, Sihan Xu, Hua Ji

  25. Spatiotemporal-aware Session-based Recommendation with Graph Neural Networks.

    Yinfeng Li, Chen Gao, Xiaoyi Du, Huazhou Wei, Hengliang Luo, Depeng Jin, Yong Li

  26. Dynamic Network Embedding via Temporal Path Adjacency Matrix Factorization.

    Zhuoming Li, Darong Lai

  27. DA-Net: Distributed Attention Network for Temporal Knowledge Graph Reasoning.

    Kangzheng Liu, Feng Zhao, Hongxu Chen, Yicong Li, Guandong Xu, Hai Jin

  28. Unsupervised Hierarchical Graph Pooling via Substructure-Sensitive Mutual Information Maximization.

    Ning Liu, Songlei Jian, Dongsheng Li, Hongzuo Xu

  29. HeGA: Heterogeneous Graph Aggregation Network for Trajectory Prediction in High-Density Traffic.

    Shuncheng Liu, Xu Chen, Ziniu Wu, Liwei Deng, Han Su, Kai Zheng

  30. I Know What You Do Not Know: Knowledge Graph Embedding via Co-distillation Learning.

    Yang Liu, Zequn Sun, Guangyao Li, Wei Hu

  31. Social Graph Transformer Networks for Pedestrian Trajectory Prediction in Complex Social Scenarios.

    Yao Liu, Lina Yao, Binghao Li, Xianzhi Wang, Claude Sammut

  32. Are Gradients on Graph Structure Reliable in Gray-box Attacks?

    Zihan Liu, Yun Luo, Lirong Wu, Siyuan Li, Zicheng Liu, Stan Z. Li

  33. HySAGE: A Hybrid Static and Adaptive Graph Embedding Network for Context-Drifting Recommendations.

    Sichun Luo, Xinyi Zhang, Yuanzhang Xiao, Linqi Song

  34. DEMO: Disentangled Molecular Graph Generation via an Invertible Flow Model.

    Changsheng Ma, Qiang Yang, Xin Gao, Xiangliang Zhang

  35. Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting.

    Yihong Ma, Patrick Gérard, Yijun Tian, Zhichun Guo, Nitesh V. Chawla

  36. Adaptive Re-Ranking with a Corpus Graph.

    Sean MacAvaney, Nicola Tonellotto, Craig Macdonald

  37. Automatic Meta-Path Discovery for Effective Graph-Based Recommendation.

    Wentao Ning, Reynold Cheng, Jiajun Shen, Nur Al Hasan Haldar, Ben Kao, Xiao Yan, Nan Huo, Wai Kit Lam, Tian Li, Bo Tang

  38. SVD-GCN: A Simplified Graph Convolution Paradigm for Recommendation.

    Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine

  39. Malicious Repositories Detection with Adversarial Heterogeneous Graph Contrastive Learning.

    Yiyue Qian, Yiming Zhang, Nitesh V. Chawla, Yanfang Ye, Chuxu Zhang

  40. Reinforced Continual Learning for Graphs.

    Appan Rakaraddi, Siew-Kei Lam, Mahardhika Pratama, Marcus de Carvalho

  41. From Known to Unknown: Quality-aware Self-improving Graph Neural Network For Open Set Social Event Detection.

    Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He

  42. Graph Based Long-Term And Short-Term Interest Model for Click-Through Rate Prediction.

    Huinan Sun, Guangliang Yu, Pengye Zhang, Bo Zhang, Xingxing Wang, Dong Wang

  43. A Self-supervised Riemannian GNN with Time Varying Curvature for Temporal Graph Learning.

    Li Sun, Junda Ye, Hao Peng, Philip S. Yu

  44. Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing.

    Qingyun Sun, Jianxin Li, Haonan Yuan, Xingcheng Fu, Hao Peng, Cheng Ji, Qian Li, Philip S. Yu

  45. Temporality- and Frequency-aware Graph Contrastive Learning for Temporal Network.

    Shiyin Tan, Jingyi You, Dongyuan Li

  46. Interpretable Emotion Analysis Based on Knowledge Graph and OCC Model.

    Shuo Wang, Yifei Zhang, Bochen Lin, Boxun Li

  47. AdaGCL: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training.

    Yili Wang, Kaixiong Zhou, Rui Miao, Ninghao Liu, Xin Wang

  48. Imbalanced Graph Classification via Graph-of-Graph Neural Networks.

    Yu Wang, Yuying Zhao, Neil Shah, Tyler Derr

  49. Dynamic Hypergraph Learning for Collaborative Filtering.

    Chunyu Wei, Jian Liang, Bing Bai, Di Liu

  50. Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding.

    Kexuan Xin, Zequn Sun, Wen Hua, Wei Hu, Jianfeng Qu, Xiaofang Zhou

  51. Taxonomy-Enhanced Graph Neural Networks.

    Lingjun Xu, Shiyin Zhang, Guojie Song, Junshan Wang, Tianshu Wu, Guojun Liu

  52. Semi-supervised Hypergraph Node Classification on Hypergraph Line Expansion.

    Chaoqi Yang, Ruijie Wang, Shuochao Yao, Tarek F. Abdelzaher

  53. GROWN+UP: A "Graph Representation Of a Webpage" Network Utilizing Pre-training.

    Benedict Yeoh, Huijuan Wang

  54. Scalable Graph Sampling on GPUs with Compressed Graph.

    Hongbo Yin, Yingxia Shao, Xupeng Miao, Yawen Li, Bin Cui

  55. The Interaction Graph Auto-encoder Network Based on Topology-aware for Transferable Recommendation.

    Ruiyun Yu, Kang Yang, Bingyang Guo

  56. Cognize Yourself: Graph Pre-Training via Core Graph Cognizing and Differentiating.

    Tao Yu, Yao Fu, Linghui Hu, Huizhao Wang, Weihao Jiang, Shiliang Pu

  57. LTE4G: Long-Tail Experts for Graph Neural Networks.

    Sukwon Yun, Kibum Kim, Kanghoon Yoon, Chanyoung Park

  58. Look Twice as Much as You Say: Scene Graph Contrastive Learning for Self-Supervised Image Caption Generation.

    Chunhui Zhang, Chao Huang, Youhuan Li, Xiangliang Zhang, Yanfang Ye, Chuxu Zhang

  59. Along the Time: Timeline-traced Embedding for Temporal Knowledge Graph Completion.

    Fuwei Zhang, Zhao Zhang, Xiang Ao, Fuzhen Zhuang, Yongjun Xu, Qing He

  60. Handling RDF Streams: Harmonizing Subgraph Matching, Adaptive Incremental Maintenance, and Matching-free Updates Together.

    Qianzhen Zhang, Deke Guo, Xiang Zhao, Lailong Luo

  61. Contrastive Knowledge Graph Error Detection.

    Qinggang Zhang, Junnan Dong, Keyu Duan, Xiao Huang, Yezi Liu, Linchuan Xu

  62. A Simple Meta-path-free Framework for Heterogeneous Network Embedding.

    Rui Zhang, Arthur Zimek, Peter Schneider-Kamp

  63. Two-Level Graph Path Reasoning for Conversational Recommendation with User Realistic Preference.

    Rongmei Zhao, Shenggen Ju, Jian Peng, Ning Yang, Fanli Yan, Siyu Sun

  64. MentorGNN: Deriving Curriculum for Pre-Training GNNs.

    Dawei Zhou, Lecheng Zheng, Dongqi Fu, Jiawei Han, Jingrui He

  65. D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation Learning.

    Honglu Zhou, Advith Chegu, Samuel S. Sohn, Zuohui Fu, Gerard de Melo, Mubbasir Kapadia

  66. Decoupled Hyperbolic Graph Attention Network for Modeling Substitutable and Complementary Item Relationships.

    Zhiheng Zhou, Tao Wang, Linfang Hou, Xinyuan Zhou, Mian Ma, Zhuoye Ding

  67. Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation.

    Jun Zhuang, Mohammad Al Hasan

  68. Tiger: Transferable Interest Graph Embedding for Domain-Level Zero-Shot Recommendation.

    Jianhuan Zhuo, Jianxun Lian, Lanling Xu, Ming Gong, Linjun Shou, Daxin Jiang, Xing Xie, Yinliang Yue

  69. Efficient and Effective SPARQL Autocompletion on Very Large Knowledge Graphs.

    Hannah Bast, Johannes Kalmbach, Theresa Klumpp, Florian Kramer, Niklas Schnelle

  70. Graph Neural Networks Pretraining Through Inherent Supervision for Molecular Property Prediction.

    Roy Benjamin, Uriel Singer, Kira Radinsky

  71. GIFT: Graph-guIded Feature Transfer for Cold-Start Video Click-Through Rate Prediction.

    Yi Cao, Sihao Hu, Yu Gong, Zhao Li, Yazheng Yang, Qingwen Liu, Shouling Ji

  72. DuETA: Traffic Congestion Propagation Pattern Modeling via Efficient Graph Learning for ETA Prediction at Baidu Maps.

    Jizhou Huang, Zhengjie Huang, Xiaomin Fang, Shikun Feng, Xuyi Chen, Jiaxiang Liu, Haitao Yuan, Haifeng Wang

  73. PlatoGL: Effective and Scalable Deep Graph Learning System for Graph-enhanced Real-Time Recommendation.

    Dandan Lin, Shijie Sun, Jingtao Ding, Xuehan Ke, Hao Gu, Xing Huang, Chonggang Song, Xuri Zhang, Lingling Yi, Jie Wen, Chuan Chen

  74. BRIGHT - Graph Neural Networks in Real-time Fraud Detection.

    Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang, Yang Zhao, Yinan Shan, Ramesh Raghunathan, Ce Zhang, Jiawei Jiang

  75. Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction.

    Sheng Xiang, Dawei Cheng, Chencheng Shang, Ying Zhang, Yuqi Liang

  76. Graph-based Weakly Supervised Framework for Semantic Relevance Learning in E-commerce.

    Zhiyuan Zeng, Yuzhi Huang, Tianshu Wu, Hongbo Deng, Jian Xu, Bo Zheng

  77. Cross-Domain Product Search with Knowledge Graph.

    Rui Zhu, Yiming Zhao, Wei Qu, Zhongyi Liu, Chenliang Li

  78. Interpretability of BERT Latent Space through Knowledge Graphs.

    Vito Walter Anelli, Giovanni Maria Biancofiore, Alessandro De Bellis, Tommaso Di Noia, Eugenio Di Sciascio

  79. CS-MLGCN: Multiplex Graph Convolutional Networks for Community Search in Multiplex Networks.

    Ali Behrouz, Farnoosh Hashemi

  80. Scalable Graph Representation Learning via Locality-Sensitive Hashing.

    Xiusi Chen, Jyun-Yu Jiang, Wei Wang

  81. On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs.

    Hejie Cui, Zijie Lu, Pan Li, Carl Yang

  82. Adaptive Graph Spatial-Temporal Transformer Network for Traffic Forecasting.

    Aosong Feng, Leandros Tassiulas

  83. Subspace Co-clustering with Two-Way Graph Convolution.

    Chakib Fettal, Lazhar Labiod, Mohamed Nadif

  84. OpenHGNN: An Open Source Toolkit for Heterogeneous Graph Neural Network.

    Hui Han, Tianyu Zhao, Cheng Yang, Hongyi Zhang, Yaoqi Liu, Xiao Wang, Chuan Shi

  85. AMinerGNN: Heterogeneous Graph Neural Network for Paper Click-through Rate Prediction with Fusion Query.

    Zepeng Huai, Zhe Wang, Yifan Zhu, Peng Zhang

  86. LGP: Few-Shot Class-Evolutionary Learning on Dynamic Graphs.

    Tiancheng Huang, Feng Zhao, Donglin Wang

  87. RealGraphGPU: A High-Performance GPU-Based Graph Engine toward Large-Scale Real-World Network Analysis.

    Myung-Hwan Jang, Yun-Yong Ko, Dongkyu Jeong, Jeong-Min Park, Sang-Wook Kim

  88. GReS: Graphical Cross-domain Recommendation for Supply Chain Platform.

    Zhiwen Jing, Ziliang Zhao, Yang Feng, Xiaochen Ma, Nan Wu, Shengqiao Kang, Cheng Yang, Yujia Zhang, Hao Guo

  89. Commonsense Knowledge Base Completion with Relational Graph Attention Network and Pre-trained Language Model.

    Jinhao Ju, Deqing Yang, Jingping Liu

  90. Models and Benchmarks for Representation Learning of Partially Observed Subgraphs.

    Dongkwan Kim, Jiho Jin, Jaimeen Ahn, Alice Oh

  91. Bootstrapped Knowledge Graph Embedding based on Neighbor Expansion.

    Jun Seon Kim, Seong-Jin Ahn, Myoung Ho Kim

  92. Debiasing Neighbor Aggregation for Graph Neural Network in Recommender Systems.

    Minseok Kim, Jinoh Oh, Jaeyoung Do, Sungjin Lee

  93. Dual-Augment Graph Neural Network for Fraud Detection.

    Qiutong Li, Yanshen He, Cong Xu, Feng Wu, Jianliang Gao, Zhao Li

  94. SmartQuery: An Active Learning Framework for Graph Neural Networks through Hybrid Uncertainty Reduction.

    Xiaoting Li, Yuhang Wu, Vineeth Rakesh, Yusan Lin, Hao Yang, Fei Wang

  95. Heterogeneous Hypergraph Neural Network for Friend Recommendation with Human Mobility.

    Yongkang Li, Zipei Fan, Jixiao Zhang, Dengheng Shi, Tianqi Xu, Du Yin, Jinliang Deng, Xuan Song

  96. Embedding Global and Local Influences for Dynamic Graphs.

    Meng Liu, Jiaming Wu, Yong Liu

  97. Memory Augmented Graph Learning Networks for Multivariate Time Series Forecasting.

    Xiangyue Liu, Xinqi Lyu, Xiangchi Zhang, Jianliang Gao, Jiamin Chen

  98. Sampling Enclosing Subgraphs for Link Prediction.

    Paul Louis, Shweta Ann Jacob, Amirali Salehi-Abari

  99. Urban Region Profiling via Multi-Graph Representation Learning.

    Yan Luo, Fu-Lai Chung, Kai Chen

  100. Improving Graph-based Document-Level Relation Extraction Model with Novel Graph Structure.

    Seongsik Park, Dongkeun Yoon, Harksoo Kim

  101. GRETEL: Graph Counterfactual Explanation Evaluation Framework.

    Mario Alfonso Prado-Romero, Giovanni Stilo

  102. Do Graph Neural Networks Build Fair User Models? Assessing Disparate Impact and Mistreatment in Behavioural User Profiling.

    Erasmo Purificato, Ludovico Boratto, Ernesto William De Luca

  103. Explainable Graph-based Fraud Detection via Neural Meta-graph Search.

    Zidi Qin, Yang Liu, Qing He, Xiang Ao

  104. A Model-Centric Explainer for Graph Neural Network based Node Classification.

    Sayan Saha, Monidipa Das, Sanghamitra Bandyopadhyay

  105. A Graph-based Spatiotemporal Model for Energy Markets.

    Swati Sharma, Srinivasan Iyengar, Shun Zheng, Kshitij Kapoor, Wei Cao, Jiang Bian, Shivkumar Kalyanaraman, John Lemmon

  106. ST-GAT: A Spatio-Temporal Graph Attention Network for Accurate Traffic Speed Prediction.

    Junho Song, Jiwon Son, Dong-hyuk Seo, Kyungsik Han, Namhyuk Kim, Sang-Wook Kim

  107. Multi-Aspect Embedding of Dynamic Graphs.

    Aimin Sun, Zhiguo Gong

  108. Leveraging the Graph Structure of Neural Network Training Dynamics.

    Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra

  109. Efficiently Answering Minimum Reachable Label Set Queries in Edge-Labeled Graphs.

    Yanping Wu, Renjie Sun, Chen Chen, Xiaoyang Wang, Xianming Fu

  110. Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty.

    Xueying Yang, Jiamian Wang, Xujiang Zhao, Sheng Li, Zhiqiang Tao

  111. An Enhanced Gated Graph Neural Network for E-commerce Recommendation.

    Jihai Zhang, Fangquan Lin, Cheng Yang, Ziqiang Cui

  112. Graph Representation Learning via Adaptive Multi-layer Neighborhood Diffusion Contrast.

    Jijie Zhang, Yan Yang, Yong Liu, Meng Han, Shaowei Yin

  113. Deep Contrastive Multiview Network Embedding.

    Mengqi Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang

  114. SuGeR: A Subgraph-based Graph Convolutional Network Method for Bundle Recommendation.

    Zhenning Zhang, Boxin Du, Hanghang Tong

  115. KSG: Knowledge and Skill Graph.

    Feng Zhao, Ziqi Zhang, Donglin Wang

  116. Spherical Graph Embedding for Item Retrieval in Recommendation System.

    Wenqiao Zhu, Yesheng Xu, Xin Huang, Qiyang Min, Xun Zhou

  117. GALGO: Scalable Graph Analytics with a Parallel DBMS.

    Wellington Cabrera, Xiantian Zhou, Ladjel Bellatreche, Carlos Ordonez

  118. DASH: An Agile Knowledge Graph System Disentangling Demands, Algorithms, Data Resources, and Humans.

    Shaowei Chen, Haoran Wang, Jie Liu, Jiahui Wu

  119. A GPU-based Graph Pattern Mining System.

    Lin Hu, Lei Zou

  120. Flurry: A Fast Framework for Provenance Graph Generation for Representation Learning.

    Maya Kapoor, Joshua Melton, Michael Ridenhour, Thomas Moyer, Siddharth Krishnan

  121. Approximate and Interactive Processing of Aggregate Queries on Knowledge Graphs: A Demonstration.

    Yuxiang Wang, Arijit Khan, Xiaoliang Xu, Shuzhan Ye, Shihuang Pan, Yuhan Zhou

  122. gCBO: A Cost-based Optimizer for Graph Databases.

    Linglin Yang, Lei Yang, Yue Pang, Lei Zou

  123. ExeKG: Executable Knowledge Graph System for User-friendly Data Analytics.

    Zhuoxun Zheng, Baifan Zhou, Dongzhuoran Zhou, Ahmet Soylu, Evgeny Kharlamov

  124. ScheRe: Schema Reshaping for Enhancing Knowledge Graph Construction.

    Dongzhuoran Zhou, Baifan Zhou, Zhuoxun Zheng, Ahmet Soylu, Ognjen Savkovic, Egor V. Kostylev, Evgeny Kharlamov

  125. Fifty Shades of Pink: Understanding Color in e-commerce using Knowledge Graphs.

    Lizzie Liang, Sneha Kamath, Petar Ristoski, Qunzhi Zhou, Zhe Wu

  126. Shoe Size Resolution in Search Queries and Product Listings using Knowledge Graphs.

    Petar Ristoski, Aritra Mandal, Simon Becker, Anu Mandalam, Ethan Hart, Sanjika Hewavitharana, Zhe Wu, Qunzhi Zhou

  127. Geographical Address Models in the Indian e-Commerce.

    Ravindra Babu Tallamraju

  128. Executable Knowledge Graph for Transparent Machine Learning in Welding Monitoring at Bosch.

    Zhuoxun Zheng, Baifan Zhou, Dongzhuoran Zhou, Ahmet Soylu, Evgeny Kharlamov

  129. Causal Relationship over Knowledge Graphs.

    Hao Huang

  130. Graph-based Management and Mining of Blockchain Data.

    Arijit Khan, Cuneyt Gurcan Akcora

  131. Mining of Real-world Hypergraphs: Patterns, Tools, and Generators.

    Geon Lee, Jaemin Yoo, Kijung Shin

  132. TrustLOG: The First Workshop on Trustworthy Learning on Graphs.

    Jian Kang, Shuaicheng Zhang, Bo Li, Jingrui He, Jian Pei, Dawei Zhou

  133. The 1st International Workshop on Federated Learning with Graph Data (FedGraph).

    Carl Yang, Xiaoxiao Li, Nathalie Baracaldo, Neil Shah, Chaoyang He, Lingjuan Lyu, Lichao Sun, Salman Avestimehr

  1. SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds

    Qingdong He, Zhengning Wang, Hao Zeng, Yi Zeng, Yijun Liu

  2. Graph-Based Point Tracker for 3D Object Tracking in Point Clouds

    Minseong Park, Hongje Seong, Wonje Jang, Euntai Kim

  3. Learning to Detect 3D Facial Landmarks via Heatmap Regression with Graph Convolutional Network

    Yuan Wang, Min Cao, Zhenfeng Fan, Silong Peng

  4. Adaptive Hypergraph Neural Network for Multi-Person Pose Estimation

    Xixia Xu, Qi Zou, Xue Lin

  5. ACGNet: Action Complement Graph Network for Weakly-Supervised Temporal Action Localization

    Zichen Yang, Jie Qin, Di Huang

  6. Hybrid Graph Neural Networks for Few-Shot Learning

    Tianyuan Yu, Sen He, Yi-Zhe Song, Tao Xiang

  7. MAGIC: Multimodal relAtional Graph adversarIal inferenCe for Diverse and Unpaired Text-Based Image Captioning

    Wenqiao Zhang, Haochen Shi, Jiannan Guo, Shengyu Zhang, Qingpeng Cai, Juncheng Li, Sihui Luo, Yueting Zhuang

  8. Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations

    Deyu Bo, Binbin Hu, Xiao Wang, Zhiqiang Zhang, Chuan Shi, Jun Zhou

  9. Differentially Describing Groups of Graphs

    Corinna Coupette, Sebastian Dalleiger, Jilles Vreeken

  10. Molecular Contrastive Learning with Chemical Element Knowledge Graph

    Yin Fang, Qiang Zhang, Haihong Yang, Xiang Zhuang, Shumin Deng, Wen Zhang, Ming Qin, Zhuo Chen, Xiaohui Fan, Huajun Chen

  11. Heterogeneity-Aware Twitter Bot Detection with Relational Graph Transformers

    Shangbin Feng, Zhaoxuan Tan, Rui Li, Minnan Luo

  12. Orthogonal Graph Neural Networks

    Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang

  13. GNN-Retro: Retrosynthetic Planning with Graph Neural Networks

    Peng Han, Peilin Zhao, Chan Lu, Junzhou Huang, Jiaxiang Wu, Shuo Shang, Bin Yao, Xiangliang Zhang

  14. Block Modeling-Guided Graph Convolutional Neural Networks

    Dongxiao He, Chundong Liang, Huixin Liu, Mingxiang Wen, Pengfei Jiao, Zhiyong Feng

  15. From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs

    Weijie Liu, Hui Qian, Chao Zhang, Jiahao Xie, Zebang Shen, Nenggan Zheng

  16. TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphs

    Yushan Liu, Yunpu Ma, Marcel Hildebrandt, Mitchell Joblin, Volker Tresp

  17. A Self-Supervised Mixed-Curvature Graph Neural Network

    Li Sun, Zhongbao Zhang, Junda Ye, Hao Peng, Jiawei Zhang, Sen Su, Philip S. Yu

  18. Graph Structure Learning with Variational Information Bottleneck

    Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu

  19. Exploring Relational Semantics for Inductive Knowledge Graph Completion

    Changjian Wang, Xiaofei Zhou, Shirui Pan, Linhua Dong, Zeliang Song, Ying Sha

  20. HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting

    Chenyu Wang, Zongyu Lin, Xiaochen Yang, Jiao Sun, Mingxuan Yue, Cyrus Shahabi

  21. Powerful Graph Convolutional Networks with Adaptive Propagation Mechanism for Homophily and Heterophily

    Tao Wang, Di Jin, Rui Wang, Dongxiao He, Yuxiao Huang

  22. CoCoS: Enhancing Semi-supervised Learning on Graphs with Unlabeled Data via Contrastive Context Sharing

    Siyue Xie, Da Sun Handason Tam, Wing Cheong Lau

  23. Unsupervised Adversarially Robust Representation Learning on Graphs

    Jiarong Xu, Yang Yang, Junru Chen, Xin Jiang, Chunping Wang, Jiangang Lu, Yizhou Sun

  24. Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs

    Jiarong Xu, Yizhou Sun, Xin Jiang, Yanhao Wang, Chunping Wang, Jiangang Lu, Yang Yang

  25. Self-Supervised Graph Neural Networks via Diverse and Interactive Message Passing

    Liang Yang, Cheng Chen, Weixun Li, Bingxin Niu, Junhua Gu, Chuan Wang, Dongxiao He, Yuanfang Guo, Xiaochun Cao

  26. Multi-Scale Distillation from Multiple Graph Neural Networks

    Chunhai Zhang, Jie Liu, Kai Dang, Wenzheng Zhang

  27. Robust Heterogeneous Graph Neural Networks against Adversarial Attacks

    Mengmei Zhang, Xiao Wang, Meiqi Zhu, Chuan Shi, Zhiqiang Zhang, Jun Zhou

  28. Multi-View Intent Disentangle Graph Networks for Bundle Recommendation

    Sen Zhao, Wei Wei, Ding Zou, Xianling Mao

  29. Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-Supervision

    Jun Zhuang, Mohammad Al Hasan

  30. GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction

    Shuangli Li, Jingbo Zhou, Tong Xu, Dejing Dou, Hui Xiong

  31. Context-Aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs

    Chang Lu, Tian Han, Yue Ning

  32. DDGCN: Dual Dynamic Graph Convolutional Networks for Rumor Detection on Social Media

    Mengzhu Sun, Xi Zhang, Jiaqi Zheng, Guixiang Ma

  33. RepBin: Constraint-Based Graph Representation Learning for Metagenomic Binning

    Hansheng Xue, Vijini Mallawaarachchi, Yujia Zhang, Vaibhav Rajan, Yu Lin

  34. ZINB-Based Graph Embedding Autoencoder for Single-Cell RNA-Seq Interpretations

    Zhuohan Yu, Yifu Lu, Yunhe Wang, Fan Tang, Ka-Chun Wong, Xiangtao Li

  35. Hierarchical Multi-Supervision Multi-Interaction Graph Attention Network for Multi-Camera Pedestrian Trajectory Prediction

    Guoliang Zhao, Yuxun Zhou, Zhanbo Xu, Yadong Zhou, Jiang Wu

  36. ER: Equivariance Regularizer for Knowledge Graph Completion

    Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Qingming Huang

  37. Geometry Interaction Knowledge Graph Embeddings

    Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang

  38. Multi-Relational Graph Representation Learning with Bayesian Gaussian Process Network

    Guanzheng Chen, Jinyuan Fang, Zaiqiao Meng, Qiang Zhang, Shangsong Liang

  39. How Does Knowledge Graph Embedding Extrapolate to Unseen Data: A Semantic Evidence View

    Ren Li, Yanan Cao, Qiannan Zhu, Guanqun Bi, Fang Fang, Yi Liu, Qian Li

  40. Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection

    Ting Long, Yutong Xie, Xianyu Chen, Weinan Zhang, Qinxiang Cao, Yong Yu

  41. TempoQR: Temporal Question Reasoning over Knowledge Graphs

    Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis, Adesoji Adeshina, Phillip R. Howard, Tetiana Grinberg, Nagib Hakim, George Karypis

  42. Learning to Walk with Dual Agents for Knowledge Graph Reasoning

    Denghui Zhang, Zixuan Yuan, Hao Liu, Xiaodong Lin, Hui Xiong

  43. Beyond GNNs: An Efficient Architecture for Graph Problems

    Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi

  44. Graph Neural Controlled Differential Equations for Traffic Forecasting

    Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang, Noseong Park

  45. Graph-Wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning

    Thilini Cooray, Ngai-Man Cheung

  46. Meta Propagation Networks for Graph Few-shot Semi-supervised Learning

    Kaize Ding, Jianling Wang, James Caverlee, Huan Liu

  47. Disentangled Spatiotemporal Graph Generative Models

    Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao

  48. Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples

    Wei Duan, Junyu Xuan, Maoying Qiao, Jie Lu

  49. KerGNNs: Interpretable Graph Neural Networks with Graph Kernels

    Aosong Feng, Chenyu You, Shiqiang Wang, Leandros Tassiulas

  50. LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks

    Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng

  51. TIGGER: Scalable Generative Modelling for Temporal Interaction Graphs

    Shubham Gupta, Sahil Manchanda, Srikanta Bedathur, Sayan Ranu

  52. Cross-Domain Few-Shot Graph Classification

    Kaveh Hassani

  53. SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data

    Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr

  54. Fast Graph Neural Tangent Kernel via Kronecker Sketching

    Shunhua Jiang, Yunze Man, Zhao Song, Zheng Yu, Danyang Zhuo

  55. Adaptive Kernel Graph Neural Network

    Mingxuan Ju, Shifu Hou, Yujie Fan, Jianan Zhao, Yanfang Ye, Liang Zhao

  56. Directed Graph Auto-Encoders

    Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Idé, Aurélie C. Lozano, Naoki Abe

  57. Augmentation-Free Self-Supervised Learning on Graphs

    Namkyeong Lee, Junseok Lee, Chanyoung Park

  58. Robust Graph-Based Multi-View Clustering

    Weixuan Liang, Xinwang Liu, Sihang Zhou, Jiyuan Liu, Siwei Wang, En Zhu

  59. On the Use of Unrealistic Predictions in Hundreds of Papers Evaluating Graph Representations

    Li-Chung Lin, Cheng-Hung Liu, Chih-Ming Chen, Kai-Chin Hsu, I-Feng Wu, Ming-Feng Tsai, Chih-Jen Lin

  60. Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching

    Xin Liu, Yangqiu Song

  61. Deep Graph Clustering via Dual Correlation Reduction

    Yue Liu, Wenxuan Tu, Sihang Zhou, Xinwang Liu, Linxuan Song, Xihong Yang, En Zhu

  62. fGOT: Graph Distances Based on Filters and Optimal Transport

    Hermina Petric Maretic, Mireille El Gheche, Giovanni Chierchia, Pascal Frossard

  63. Temporal Knowledge Graph Completion Using Box Embeddings

    Johannes Messner, Ralph Abboud, Ismail Ilkan Ceylan

  64. Simple Unsupervised Graph Representation Learning

    Yujie Mo, Liang Peng, Jie Xu, Xiaoshuang Shi, Xiaofeng Zhu

  65. Bag Graph: Multiple Instance Learning Using Bayesian Graph Neural Networks

    Soumyasundar Pal, Antonios Valkanas, Florence Regol, Mark Coates

  66. Deformable Graph Convolutional Networks

    Jinyoung Park, Sungdong Yoo, Jihwan Park, Hyunwoo J. Kim

  67. Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation

    Joonhyung Park, Hajin Shim, Eunho Yang

  68. Interpretable Neural Subgraph Matching for Graph Retrieval

    Indradyumna Roy, Venkata Sai Baba Reddy Velugoti, Soumen Chakrabarti, Abir De

  69. Hypergraph Modeling via Spectral Embedding Connection: Hypergraph Cut, Weighted Kernel k-Means, and Heat Kernel

    Shota Saito

  70. VACA: Designing Variational Graph Autoencoders for Causal Queries

    Pablo Sánchez-Martín, Miriam Rateike, Isabel Valera

  71. Graph Filtration Kernels

    Till Hendrik Schulz, Pascal Welke, Stefan Wrobel

  72. EqGNN: Equalized Node Opportunity in Graphs

    Uriel Singer, Kira Radinsky

  73. Graph Pointer Neural Networks

    Tianmeng Yang, Yujing Wang, Zhihan Yue, Yaming Yang, Yunhai Tong, Jing Bai

  74. AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators

    Yihang Yin, Qingzhong Wang, Siyu Huang, Haoyi Xiong, Xiang Zhang

  75. Early-Bird GCNs: Graph-Network Co-optimization towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets

    Haoran You, Zhihan Lu, Zijian Zhou, Yonggan Fu, Yingyan Lin

  76. SAIL: Self-Augmented Graph Contrastive Learning

    Lu Yu, Shichao Pei, Lizhong Ding, Jun Zhou, Longfei Li, Chuxu Zhang, Xiangliang Zhang

  77. Low-Pass Graph Convolutional Network for Recommendation

    Wenhui Yu, Zixin Zhang, Zheng Qin

  78. Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning

    Yuheng Zhang, Hanghang Tong, Yinglong Xia, Yan Zhu, Yuejie Chi, Lei Ying

  79. ProtGNN: Towards Self-Explaining Graph Neural Networks

    Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Cheekong Lee

  80. Structural Landmarking and Interaction Modelling: A "SLIM" Network for Graph Classification

    Yaokang Zhu, Kai Zhang, Jun Wang, Haibin Ling, Jie Zhang, Hongyuan Zha

  81. Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs

    Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen

  82. Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability Using Tree Search and Graph Neural Networks

    Kevin Osanlou, Jeremy Frank, Andrei Bursuc, Tristan Cazenave, Eric Jacopin, Christophe Guettier, J. Benton

  83. Qubit Routing Using Graph Neural Network Aided Monte Carlo Tree Search

    Animesh Sinha, Utkarsh Azad, Harjinder Singh

  84. Enhanced Story Comprehension for Large Language Models through Dynamic Document-Based Knowledge Graphs

    Berkeley R. Andrus, Yeganeh Nasiri, Shilong Cui, Benjamin Cullen, Nancy Fulda

  85. ISEEQ: Information Seeking Question Generation Using Dynamic Meta-Information Retrieval and Knowledge Graphs

    Manas Gaur, Kalpa Gunaratna, Vijay Srinivasan, Hongxia Jin

  86. Dynamic Key-Value Memory Enhanced Multi-Step Graph Reasoning for Knowledge-Based Visual Question Answering

    Mingxiao Li, Marie-Francine Moens

  87. LeSICiN: A Heterogeneous Graph-Based Approach for Automatic Legal Statute Identification from Indian Legal Documents

    Shounak Paul, Pawan Goyal, Saptarshi Ghosh

  88. Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification

    Yinhua Piao, Sangseon Lee, Dohoon Lee, Sun Kim

  89. Hierarchical Heterogeneous Graph Attention Network for Syntax-Aware Summarization

    Zixing Song, Irwin King

  90. DisenCite: Graph-Based Disentangled Representation Learning for Context-Specific Citation Generation

    Yifan Wang, Yiping Song, Shuai Li, Chaoran Cheng, Wei Ju, Ming Zhang, Sheng Wang

  91. GraphMemDialog: Optimizing End-to-End Task-Oriented Dialog Systems Using Graph Memory Networks

    Jie Wu, Ian G. Harris, Hongzhi Zhao

  92. A Graph Convolutional Network with Adaptive Graph Generation and Channel Selection for Event Detection

    Zhipeng Xie, Yumin Tu

  93. JAKET: Joint Pre-training of Knowledge Graph and Language Understanding

    Donghan Yu, Chenguang Zhu, Yiming Yang, Michael Zeng

  94. CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting

    Lijing Wang, Aniruddha Adiga, Jiangzhuo Chen, Adam Sadilek, Srinivasan Venkatramanan, Madhav V. Marathe

  95. Accelerating COVID-19 Research with Graph Mining and Transformer-Based Learning

    Ilya Tyagin, Ankit Kulshrestha, Justin Sybrandt, Krish Matta, Michael Shtutman, Ilya Safro

  1. A New Perspective on "How Graph Neural Networks Go Beyond Weisfeiler-Lehman?".

    Asiri Wijesinghe, Qing Wang

  2. Data-Efficient Graph Grammar Learning for Molecular Generation.

    Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik

  3. Expressiveness and Approximation Properties of Graph Neural Networks.

    Floris Geerts, Juan L. Reutter

  4. Understanding over-squashing and bottlenecks on graphs via curvature.

    Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein

  5. Is Homophily a Necessity for Graph Neural Networks?

    Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang

  6. DEGREE: Decomposition Based Explanation for Graph Neural Networks.

    Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu

  7. Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations.

    Anuroop Sriram, Abhishek Das, Brandon M. Wood, Siddharth Goyal, C. Lawrence Zitnick

  8. On Evaluation Metrics for Graph Generative Models.

    Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W. Taylor

  9. Graph Condensation for Graph Neural Networks.

    Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah

  10. From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness.

    Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah

  11. Triangle and Four Cycle Counting with Predictions in Graph Streams.

    Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang

  12. NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs.

    Mikhail Galkin, Etienne G. Denis, Jiapeng Wu, William L. Hamilton

  13. Graphon based Clustering and Testing of Networks: Algorithms and Theory.

    Mahalakshmi Sabanayagam, Leena Chennuru Vankadara, Debarghya Ghoshdastidar

  14. How Attentive are Graph Attention Networks?

    Shaked Brody, Uri Alon, Eran Yahav

  15. Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation.

    Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah

  16. Large-Scale Representation Learning on Graphs via Bootstrapping.

    Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L. Dyer, Rémi Munos, Petar Velickovic, Michal Valko

  17. Top-N: Equivariant Set and Graph Generation without Exchangeability.

    Clément Vignac, Pascal Frossard

  18. PF-GNN: Differentiable particle filtering based approximation of universal graph representations.

    Mohammed Haroon Dupty, Yanfei Dong, Wee Sun Lee

  19. Equivariant Graph Mechanics Networks with Constraints.

    Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang

  20. Convergent Graph Solvers.

    Junyoung Park, Jinhyun Choo, Jinkyoo Park

  21. GLASS: GNN with Labeling Tricks for Subgraph Representation Learning.

    Xiyuan Wang, Muhan Zhang

  22. Space-Time Graph Neural Networks.

    Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro

  23. End-to-End Learning of Probabilistic Hierarchies on Graphs.

    Daniel Zügner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Günnemann

  24. GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification.

    Joonhyung Park, Jaeyun Song, Eunho Yang

  25. Why Propagate Alone? Parallel Use of Labels and Features on Graphs.

    Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf

  26. Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks.

    Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li

  27. Query Embedding on Hyper-Relational Knowledge Graphs.

    Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin

  28. Inductive Relation Prediction Using Analogy Subgraph Embeddings.

    Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan

  29. Graph Neural Network Guided Local Search for the Traveling Salesperson Problem.

    Benjamin Hudson, Qingbiao Li, Matthew Malencia, Amanda Prorok

  30. Understanding and Improving Graph Injection Attack by Promoting Unnoticeability.

    Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng

  31. Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis.

    Siyi Tang, Jared Dunnmon, Khaled Kamal Saab, Xuan Zhang, Qianying Huang, Florian Dubost, Daniel L. Rubin, Christopher Lee-Messer

  32. EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression.

    Zirui Liu, Kaixiong Zhou, Fan Yang, Li Li, Rui Chen, Xia Hu

  33. Graph-Relational Domain Adaptation.

    Zihao Xu, Hao He, Guang-He Lee, Bernie Wang, Hao Wang

  34. PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication.

    Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin

  35. Graph Neural Networks with Learnable Structural and Positional Representations.

    Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson

  36. Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction.

    Mingyue Tang, Pan Li, Carl Yang

  37. Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective.

    Wei Huang, Yayong Li, Weitao Du, Richard Y. D. Xu, Jie Yin, Ling Chen, Miao Zhang

  38. Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks.

    Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam

  39. Neural Methods for Logical Reasoning over Knowledge Graphs.

    Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, Ce Zhang

  40. Graph-Guided Network for Irregularly Sampled Multivariate Time Series.

    Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik

  41. Explainable GNN-Based Models over Knowledge Graphs.

    David Jaime Tena Cucala, Bernardo Cuenca Grau, Egor V. Kostylev, Boris Motik

  42. Pre-training Molecular Graph Representation with 3D Geometry.

    Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang

  43. GRAND++: Graph Neural Diffusion with A Source Term.

    Matthew Thorpe, Tan Minh Nguyen, Hedi Xia, Thomas Strohmer, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang

  44. Semi-relaxed Gromov-Wasserstein divergence and applications on graphs.

    Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty

  45. Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms.

    Simin Hong, Anthony G. Cohn, David Crossland Hogg

  46. Learning Graphon Mean Field Games and Approximate Nash Equilibria.

    Kai Cui, Heinz Koeppl

  47. Topological Graph Neural Networks.

    Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt

  48. Automated Self-Supervised Learning for Graphs.

    Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang

  49. You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks.

    Eli Chien, Chao Pan, Jianhao Peng, Olgica Milenkovic

  50. Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods.

    Wenqing Zheng, Edward W. Huang, Nikhil Rao, Sumeet Katariya, Zhangyang Wang, Karthik Subbian

  51. Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery.

    Yulun Wu, Nicholas Choma, Andrew Deru Chen, Mikaela Cashman, Érica Teixeira Prates, Verónica G. Melesse Vergara, Manesh Shah, Austin Clyde, Thomas S. Brettin, Wibe Albert de Jong, Neeraj Kumar, Martha S. Head, Rick L. Stevens, Peter Nugent, Daniel A. Jacobson, James B. Brown

  52. Spherical Message Passing for 3D Molecular Graphs.

    Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji

  53. Fairness Guarantees under Demographic Shift.

    Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum

  54. Learning Guarantees for Graph Convolutional Networks on the Stochastic Block Model.

    Wei Lu

  55. Graph-based Nearest Neighbor Search in Hyperbolic Spaces.

    Liudmila Prokhorenkova, Dmitry Baranchuk, Nikolay Bogachev, Yury Demidovich, Alexander Kolpakov

  56. Discovering Invariant Rationales for Graph Neural Networks.

    Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua

  57. Do We Need Anisotropic Graph Neural Networks?

    Shyam A. Tailor, Felix L. Opolka, Pietro Liò, Nicholas Donald Lane

  58. Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond.

    Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia

  59. Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks.

    Andrea Cini, Ivan Marisca, Cesare Alippi

  60. Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels.

    Wentao Zhang, Yexin Wang, Zhenbang You, Meng Cao, Ping Huang, Jiulong Shan, Zhi Yang, Bin Cui

  61. Handling Distribution Shifts on Graphs: An Invariance Perspective.

    Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf

  62. Generalized Demographic Parity for Group Fairness.

    Zhimeng Jiang, Xiaotian Han, Chao Fan, Fan Yang, Ali Mostafavi, Xia Hu

  63. Fixed Neural Network Steganography: Train the images, not the network.

    Varsha Kishore, Xiangyu Chen, Yan Wang, Boyi Li, Kilian Q. Weinberger

  64. A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease.

    Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Daniel R. Weinberger, Archana Venkataraman

  65. Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph.

    Dacheng Yin, Xuanchi Ren, Chong Luo, Yuwang Wang, Zhiwei Xiong, Wenjun Zeng

  66. GNN is a Counter? Revisiting GNN for Question Answering.

    Kuan Wang, Yuyu Zhang, Diyi Yang, Le Song, Tao Qin

  67. Neural graphical modelling in continuous-time: consistency guarantees and algorithms.

    Alexis Bellot, Kim Branson, Mihaela van der Schaar

  68. Learning to Schedule Learning rate with Graph Neural Networks.

    Yuanhao Xiong, Li-Cheng Lan, Xiangning Chen, Ruochen Wang, Cho-Jui Hsieh

  69. GreaseLM: Graph REASoning Enhanced Language Models.

    Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher D. Manning, Jure Leskovec

  70. Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features.

    Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf

  71. TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting.

    Yuzhou Chen, Ignacio Segovia-Dominguez, Baris Coskunuzer, Yulia R. Gel

  72. GNN-LM: Language Modeling based on Global Contexts via GNN.

    Yuxian Meng, Shi Zong, Xiaoya Li, Xiaofei Sun, Tianwei Zhang, Fei Wu, Jiwei Li

  73. Revisiting Over-smoothing in BERT from the Perspective of Graph.

    Han Shi, Jiahui Gao, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen M. S. Lee, James T. Kwok

  74. Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series.

    Enyan Dai, Jie Chen

  75. Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design.

    Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola

  76. Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions.

    Nicholas Gao, Stephan Günnemann

  77. Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions.

    Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt

  78. Context-Aware Sparse Deep Coordination Graphs.

    Tonghan Wang, Liang Zeng, Weijun Dong, Qianlan Yang, Yang Yu, Chongjie Zhang

  79. Spanning Tree-based Graph Generation for Molecules.

    Sungsoo Ahn, Binghong Chen, Tianzhe Wang, Le Song

  80. Equivariant Subgraph Aggregation Networks.

    Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron

  1. Graph Collaborative Reasoning

    Hanxiong Chen, Yunqi Li, Shaoyun Shi, Shuchang Liu, He Zhu, Yongfeng Zhang

  2. Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation

    Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jianye Hao, Irwin King

  3. Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels

    Enyan Dai, Wei Jin, Hui Liu, Suhang Wang

  4. Predicting Human Mobility via Graph Convolutional Dual-attentive Networks

    Weizhen Dang, Haibo Wang, Shirui Pan, Pei Zhang, Chuan Zhou, Xin Chen, Jilong Wang

  5. Efficient Graph Convolution for Joint Node Representation Learning and Clustering

    Chakib Fettal, Lazhar Labiod, Mohamed Nadif

  6. HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling

    Shen Gao, Yuchi Zhang, Yongliang Wang, Yang Dong, Xiuying Chen, Dongyan Zhao, Rui Yan

  7. Multi-Scale Variational Graph AutoEncoder for Link Prediction

    Zhihao Guo, Feng Wang, Kaixuan Yao, Jiye Liang, Zhiqiang Wang

  8. Outside In: Market-aware Heterogeneous Graph Neural Network for Employee Turnover Prediction

    Jinquan Hang, Zheng Dong, Hongke Zhao, Xin Song, Peng Wang, Hengshu Zhu

  9. Triangle Graph Interest Network for Click-through Rate Prediction

    Wensen Jiang, Yizhu Jiao, Qingqin Wang, Chuanming Liang, Lijie Guo, Yao Zhang, Zhijun Sun, Yun Xiong, Yangyong Zhu

  10. KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification

    Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang

  11. GAGE: Geometry Preserving Attributed Graph Embeddings

    Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos

  12. Graph Embedding with Hierarchical Attentive Membership

    Lu Lin, Ethan Blaser, Hongning Wang

  13. Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks

    Zihan Liu, Yun Luo, Zelin Zang, Stan Z. Li

  14. Ada-GNN: Adapting to Local Patterns for Improving Graph Neural Networks

    Zihan Luo, Jianxun Lian, Hong Huang, Hai Jin, Xing Xie

  15. ComGA: Community-Aware Attributed Graph Anomaly Detection

    Xuexiong Luo, Jia Wu, Amin Beheshti, Jian Yang, Xiankun Zhang, Yuan Wang, Shan Xue

  16. Learning Fair Node Representations with Graph Counterfactual Fairness

    Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li

  17. Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation

    Rongrong Ma, Guansong Pang, Ling Chen, Anton van den Hengel

  18. Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation

    Yitong Pang, Lingfei Wu, Qi Shen, Yiming Zhang, Zhihua Wei, Fangli Xu, Ethan Chang, Bo Long, Jian Pei

  19. EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning over Temporal Knowledge Graphs

    Namyong Park, Fuchen Liu, Purvanshi Mehta, Dana Cristofor, Christos Faloutsos, Yuxiao Dong

  20. Attributed Graph Modeling with Vertex Replacement Grammars

    Satyaki Sikdar, Neil Shah, Tim Weninger

  21. Graph Few-shot Class-incremental Learning

    Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu

  22. Friend Story Ranking with Edge-Contextual Local Graph Convolutions

    Xianfeng Tang, Yozen Liu, Xinran He, Suhang Wang, Neil Shah

  23. Scalable Graph Topology Learning via Spectral Densification

    Yongyu Wang, Zhiqiang Zhao, Zhuo Feng

  24. Profiling the Design Space for Graph Neural Networks based Collaborative Filtering

    Zhenyi Wang, Huan Zhao, Chuan Shi

  25. Interpretable Relation Learning on Heterogeneous Graphs

    Qiang Yang, Qiannan Zhang, Chuxu Zhang, Xiangliang Zhang

  26. Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations

    Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

  27. Community Trend Prediction on Heterogeneous Graph in E-commerce

    Jiahao Yuan, Zhao Li, Pengcheng Zou, Xuan Gao, Jinwei Pan, Wendi Ji, Xiaoling Wang

  28. Learning Concept Prerequisite Relations from Educational Data via Multi-Head Attention Variational Graph Auto-Encoders

    Juntao Zhang, Nanzhou Lin, Xuelong Zhang, Wei Song, Xiandi Yang, Zhiyong Peng

  29. Joint Learning of E-commerce Search and Recommendation with a Unified Graph Neural Network

    Kai Zhao, Yukun Zheng, Tao Zhuang, Xiang Li, Xiaoyi Zeng

  30. DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning

    Yushan Zhu, Wen Zhang, Mingyang Chen, Hui Chen, Xu Cheng, Wei Zhang, Huajun Chen

  31. A Neighborhood-Attention Fine-grained Entity Typing for Knowledge Graph Completion

    Jianhuan Zhuo, Qiannan Zhu, Yinliang Yue, Yuhong Zhao, Weisi Han

  1. Modeling User Behavior with Graph Convolution for Personalized Product Search

    Lu Fan, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang

  2. IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search

    Dian Cheng, Jiawei Chen, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng, Xiangnan He

  3. Efficient and Effective Similarity Search over Bipartite Graphs

    Renchi Yang

  4. RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary Graph

    Ruijie Wang, Zheng Li, Danqing Zhang, Qingyu Yin, Tong Zhao, Bing Yin, Tarek F. Abdelzaher

  5. TTAGN: Temporal Transaction Aggregation Graph Network for Ethereum Phishing Scams Detection

    Sijia Li, Gaopeng Gou, Chang Liu, Chengshang Hou, Zhenzhen Li, Gang Xiong

  6. ALLIE: Active Learning on Large-scale Imbalanced Graphs

    Limeng Cui, Xianfeng Tang, Sumeet Katariya, Nikhil Rao, Pallav Agrawal, Karthik Subbian, Dongwon Lee

  7. Rethinking Graph Convolutional Networks in Knowledge Graph Completion

    Zhanqiu Zhang, Jie Wang, Jieping Ye, Feng Wu

  8. Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional Knowledge Graph Embeddings

    Kai Wang, Yu Liu, Quan Z. Sheng

  9. SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs

    Xiao Liu, Haoyun Hong, Xinghao Wang, Zeyi Chen, Evgeny Kharlamov, Yuxiao Dong, Jie Tang

  10. Knowledge Graph Reasoning with Relational Digraph

    Yongqi Zhang, Quanming Yao

  11. Path Language Modeling over Knowledge Graphs for Explainable Recommendation

    Shijie Geng, Zuohui Fu, Juntao Tan, Yingqiang Ge, Gerard de Melo, Yongfeng Zhang

  12. Trustworthy Knowledge Graph Completion Based on Multi-sourced Noisy Data

    Jiacheng Huang, Yao Zhao, Wei Hu, Zhen Ning, Qijin Chen, Xiaoxia Qiu, Chengfu Huo, Weijun Ren

  13. Can Machine Translation be a Reasonable Alternative for Multilingual Question Answering Systems over Knowledge Graphs

    Aleksandr Perevalov, Andreas Both, Dennis Diefenbach, Axel-Cyrille Ngonga Ngomo

  14. Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning

    Juntao Tan, Shijie Geng, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Yunqi Li, Yongfeng Zhang

  15. An Invertible Graph Diffusion Neural Network for Source Localization

    Junxiang Wang, Junji Jiang, Liang Zhao

  16. SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation

    Jun Xia, Lirong Wu, Jintao Chen, Bozhen Hu, Stan Z. Li

  17. MiDaS: Representative Sampling from Real-world Hypergraphs

    Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, Kijung Shin

  18. CGC: Contrastive Graph Clustering for Community Detection and Tracking

    Namyong Park, Ryan A. Rossi, Eunyee Koh, Iftikhar Ahamath Burhanuddin, Sungchul Kim, Fan Du, Nesreen K. Ahmed, Christos Faloutsos

  19. Graph Neural Networks Beyond Compromise Between Attribute and Topology

    Liang Yang, Wenmiao Zhou, Weihang Peng, Bingxin Niu, Junhua Gu, Chuan Wang, Xiaochun Cao, Dongxiao He

  20. Graph Sanitation with Application to Node Classification

    Zhe Xu, Boxin Du, Hanghang Tong

  21. TREND: TempoRal Event and Node Dynamics for Graph Representation Learning

    Zhihao Wen, Yuan Fang

  22. Resource-Efficient Training for Large Graph Convolutional Networks with Label-Centric Cumulative Sampling

    Mingkai Lin, Wenzhong Li, Ding Li, Yizhou Chen, Sanglu Lu

  23. Graph Communal Contrastive Learning

    Bolian Li, Baoyu Jing, Hanghang Tong

  24. Geometric Graph Representation Learning via Maximizing Rate Reduction

    Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu

  25. Dual Space Graph Contrastive Learning

    Haoran Yang, Hongxu Chen, Shirui Pan, Lin Li, Philip S. Yu, Guandong Xu

  26. Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift

    Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou

  27. EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks

    Yushun Dong, Ninghao Liu, Brian Jalaian, Jundong Li

  28. Meta-Weight Graph Neural Network: Push the Limits Beyond Global Homophily

    Xiaojun Ma, Qin Chen, Yuanyi Ren, Guojie Song, Liang Wang

  29. Model-Agnostic Augmentation for Accurate Graph Classification

    Jaemin Yoo, Sooyeon Shim, U Kang

  30. Multimodal Continual Graph Learning with Neural Architecture Search

    Jie Cai, Xin Wang, Chaoyu Guan, Yateng Tang, Jin Xu, Bin Zhong, Wenwu Zhu

  31. AUC-oriented Graph Neural Network for Fraud Detection

    Mengda Huang, Yang Liu, Xiang Ao, Kuan Li, Jianfeng Chi, Jinghua Feng, Hao Yang, Qing He

  32. Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation

    Sixiao Zhang, Hongxu Chen, Xiangguo Sun, Yicong Li, Guandong Xu

  33. Graph-adaptive Rectified Linear Unit for Graph Neural Networks

    Yifei Zhang, Hao Zhu, Ziqiao Meng, Piotr Koniusz, Irwin King

  34. Robust Self-Supervised Structural Graph Neural Network for Social Network Prediction

    Yanfu Zhang, Hongchang Gao, Jian Pei, Heng Huang

  35. Adversarial Graph Contrastive Learning with Information Regularization

    Shengyu Feng, Baoyu Jing, Yada Zhu, Hanghang Tong

  36. Designing the Topology of Graph Neural Networks: A Novel Feature Fusion Perspective

    Lanning Wei, Huan Zhao, Zhiqiang He

  37. Towards Unsupervised Deep Graph Structure Learning

    Yixin Liu, Yu Zheng, Daokun Zhang, Hongxu Chen, Hao Peng, Shirui Pan

  38. Polarized Graph Neural Networks

    Zheng Fang, Lingjun Xu, Guojie Song, Qingqing Long, Yingxue Zhang

  39. Unbiased Graph Embedding with Biased Graph Observations

    Nan Wang, Lu Lin, Jundong Li, Hongning Wang

  40. Prohibited Item Detection via Risk Graph Structure Learning

    Yugang Ji, Guanyi Chu, Xiao Wang, Chuan Shi, Jianan Zhao, Junping Du

  41. Inflation Improves Graph Neural Networks

    Dongxiao He, Rui Guo, Xiaobao Wang, Di Jin, Yuxiao Huang, Wenjun Wang

  42. Generating Simple Directed Social Network Graphs for Information Spreading

    Christoph Schweimer, Christine Gfrerer, Florian Lugstein, David Pape, Jan A. Velimsky, Robert Elsässer, Bernhard C. Geiger

  43. On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks

    Zemin Liu, Qiheng Mao, Chenghao Liu, Yuan Fang, Jianling Sun

  44. Curvature Graph Generative Adversarial Networks

    Jianxin Li, Xingcheng Fu, Qingyun Sun, Cheng Ji, Jiajun Tan, Jia Wu, Hao Peng

  45. Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices

    Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra

  46. GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily

    Lun Du, Xiaozhou Shi, Qiang Fu, Xiaojun Ma, Hengyu Liu, Shi Han, Dongmei Zhang

  47. Compact Graph Structure Learning via Mutual Information Compression

    Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi

  48. ClusterSCL: Cluster-Aware Supervised Contrastive Learning on Graphs

    Yanling Wang, Jing Zhang, Haoyang Li, Yuxiao Dong, Hongzhi Yin, Cuiping Li, Hong Chen

  49. Graph Neural Network for Higher-Order Dependency Networks

    Di Jin, Yingli Gong, Zhiqiang Wang, Zhizhi Yu, Dongxiao He, Yuxiao Huang, Wenjun Wang

  50. PaSca: A Graph Neural Architecture Search System under the Scalable Paradigm

    Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui

  51. Element-guided Temporal Graph Representation Learning for Temporal Sets Prediction

    Le Yu, Guanghui Wu, Leilei Sun, Bowen Du, Weifeng Lv

  52. Hypercomplex Graph Collaborative Filtering

    Anchen Li, Bo Yang, Huan Huo, Farookh Khadeer Hussain

  53. Graph Neural Transport Networks with Non-local Attentions for Recommender Systems

    Huiyuan Chen, Chin-Chia Michael Yeh, Fei Wang, Hao Yang

  54. Multi-level Recommendation Reasoning over Knowledge Graphs with Reinforcement Learning

    Xiting Wang, Kunpeng Liu, Dongjie Wang, Le Wu, Yanjie Fu, Xing Xie

  55. GSL4Rec: Session-based Recommendations with Collective Graph Structure Learning and Next Interaction Prediction

    Chunyu Wei, Bing Bai, Kun Bai, Fei Wang

  56. Graph-based Extractive Explainer for Recommendations

    Peng Wang, Renqin Cai, Hongning Wang

  57. Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning

    Zihan Lin, Changxin Tian, Yupeng Hou, Wayne Xin Zhao

  58. Evidence-aware Fake News Detection with Graph Neural Networks

    Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu, Liang Wang

  59. Rumor Detection on Social Media with Graph Adversarial Contrastive Learning

    Tiening Sun, Zhong Qian, Sujun Dong, Peifeng Li, Qiaoming Zhu

  60. VisGNN: Personalized Visualization Recommendationvia Graph Neural Networks

    Fayokemi Ojo, Ryan A. Rossi, Jane Hoffswell, Shunan Guo, Fan Du, Sungchul Kim, Chang Xiao, Eunyee Koh

  61. Revisiting Graph based Social Recommendation: A Distillation Enhanced Social Graph Network

    Ye Tao, Ying Li, Su Zhang, Zhirong Hou, Zhonghai Wu

  62. DiriE: Knowledge Graph Embedding with Dirichlet Distribution

    Feiyang Wang, Zhongbao Zhang, Li Sun, Junda Ye, Yang Yan

  63. STAM: A Spatiotemporal Aggregation Method for Graph Neural Network-based Recommendation

    Zhen Yang, Ming Ding, Bin Xu, Hongxia Yang, Jie Tang

  64. GRAND+: Scalable Graph Random Neural Networks

    Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang

  65. Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network

    Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu

  66. Learning Privacy-Preserving Graph Convolutional Network with Partially Observed Sensitive Attributes

    Hui Hu, Lu Cheng, Jayden Parker Vap, Mike Borowczak

  1. BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection

    Yulin Zhu, Yuni Lai, Kaifa Zhao, Xiapu Luo, Mingquan Yuan, Jian Ren, Kai Zhou

  2. Accurate and Scalable Graph Neural Networks for Billion-Scale Graphs

    Juxiang Zeng, Pinghui Wang, Lin Lan, Junzhou Zhao, Feiyang Sun, Jing Tao, Junlan Feng, Min Hu, Xiaohong Guan

  3. Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation

    Yankai Chen, Yaming Yang, Yujing Wang, Jing Bai, Xiangchen Song, Irwin King

  4. Academic Expert Finding via $(k, \mathcal{P})$-Core based Embedding over Heterogeneous Graphs

    Xiaoliang Xu, Jun Liu, Yuxiang Wang, Xiangyu Ke

  5. AutoHEnsGNN: Winning Solution to AutoGraph Challenge for KDD Cup 2020

    Jin Xu, Mingjian Chen, Jianqiang Huang, Xingyuan Tang, Ke Hu, Jian Li, Jia Cheng, Jun Lei

  6. SLUGGER: Lossless Hierarchical Summarization of Massive Graphs

    Kyuhan Lee, Jihoon Ko, Kijung Shin

  7. $O^{2}$-SiteRec: Store Site Recommendation under the O2O Model via Multi-graph Attention Networks

    Hua Yan, Shuai Wang, Yu Yang, Baoshen Guo, Tian He, Desheng Zhang

  8. A Data-Driven Spatial-Temporal Graph Neural Network for Docked Bike Prediction

    Guanyao Li, Xiaofeng Wang, Gunarto Sindoro Njoo, Shuhan Zhong, S.-H. Gary Chan, Chih-Chieh Hung, Wen-Chih Peng

  9. Black-box Adversarial Attack and Defense on Graph Neural Networks

    Haoyang Li, Shimin Di, Zijian Li, Lei Chen, Jiannong Cao

  10. MAD-SGCN: Multivariate Anomaly Detection with Self-learning Graph Convolutional Networks

    Panpan Qi, Dan Li, See-Kiong Ng

  11. On Compressing Temporal Graphs

    Panagiotis Liakos, Katia Papakonstantinopoulou, Theodore Stefou, Alex Delis

  12. Dynamic Hypergraph Convolutional Network

    Nan Yin, Fuli Feng, Zhigang Luo, Xiang Zhang, Wenjie Wang, Xiao Luo, Chong Chen, Xian-Sheng Hua

  13. PSP: Progressive Space Pruning for Efficient Graph Neural Architecture Search

    Guanghui Zhu, Wenjie Wang, Zhuoer Xu, Feng Cheng, Mengchuan Qiu, Chunfeng Yuan, Yihua Huang

  14. HET-KG: Communication-Efficient Knowledge Graph Embedding Training via Hotness-Aware Cache

    Sicong Dong, Xupeng Miao, Pengkai Liu, Xin Wang, Bin Cui, Jianxin Li

  15. Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction

    Zhonghang Li, Chao Huang, Lianghao Xia, Yong Xu, Jian Pei

  16. BA-GNN: On Learning Bias-Aware Graph Neural Network

    Zhengyu Chen, Teng Xiao, Kun Kuang

  17. VICS-GNN: A Visual Interactive System for Community Search via Graph Neural Network

    Jiazun Chen, Jun Gao

  18. Tower Bridge Net (TB-Net): Bidirectional Knowledge Graph Aware Embedding Propagation for Explainable Recommender Systems

    Shendi Wang, Haoyang Li, Caleb Chen Cao, Xiao-Hui Li, Ng Ngai Fai, Jianxin Liu, Xun Xue, Hu Song, Jinyu Li, Guangye Gu, Lei Chen

  19. Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commerce

    Borui Ye, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Youqiang He, Kai Huang, Jun Zhou, Yanming Fang

  1. Entity Resolution with Hierarchical Graph Attention Networks

    Dezhong Yao, Yuhong Gu, Gao Cong, Hai Jin, Xinqiao Lv

  2. Compact Walks: Taming Knowledge-Graph Embeddings with Domain- and Task-Specific Pathways

    Pei-Yu Hou, Daniel Robert Korn, Cleber C. Melo-Filho, David R. Wright, Alexander Tropsha, Rada Chirkova

  3. Explaining Link Prediction Systems based on Knowledge Graph Embeddings

    Andrea Rossi, Donatella Firmani, Paolo Merialdo, Tommaso Teofili