[NeurIPS2023] Learning on Graphs

Title	OpenReview	Authors
Generative Pre-Training of Spatio-Temporal Graph Neural Networks	here	Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang
Modeling Dynamics over Meshes with Gauge Equivariant Nonlinear Message Passing	here	Jung Yeon Park, Lawson Wong, Robin Walters
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data	here	Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan
Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment	here	Yutong Xia, Yuxuan Liang, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann
Live Graph Lab: Towards Open, Dynamic and Real Transaction Graphs with NFT	here	Zhen Zhang, Bingqiao Luo, Shengliang Lu, Bingsheng He
Layer-Neighbor Sampling --- Defusing Neighborhood Explosion in GNNs	here	Muhammed Fatih Balin, Ümit Çatalyürek
Three Iterations of (d − 1)-WL Test Distinguish Non Isometric Clouds of d-dimensional Points	here	Valentino Delle Rose, Alexander Kozachinskiy, Cristobal Rojas, Mircea Petrache, Pablo Barceló
GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels	here	Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan
Can Language Models Solve Graph Problems in Natural Language?	here	Heng Wang, Shangbin Feng, Tianxing He, Zhaoxuan Tan, Xiaochuang Han, Yulia Tsvetkov
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem	here	Tal Amir, Steven Gortler, Ilai Avni, Ravina Ravina, Nadav Dym
AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity	here	Jingyuan Li, Leo Scholl, Trung Le, Pavithra Rajeswaran, Amy Orsborn, Eli Shlizerman
HyTrel: Hypergraph-enhanced Tabular Data Representation Learning	here	Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network	here	Yixiao Zhou, Ruiqi Jia, Hongxiang Lin, Hefeng Quan, Yumeng Zhao, Xiaoqing Lyu
Does Graph Distillation See Like Vision Dataset Counterpart?	here	Beining Yang, Kai Wang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Hao Tang, Yang You, Jianxin Li
How to Turn Your Knowledge Graph Embeddings into Generative Models	here	Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari
AutoGO: Automated Computation Graph Optimization for Neural Network Evolution	here	Mohammad Salameh, Keith Mills, Negar Hassanpour, Fred Han, Shuting Zhang, Wei Lu, Shangling Jui, CHUNHUA ZHOU, Fengyu Sun, Di Niu
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching	here	Duy M. H. Nguyen, Hoang Nguyen, Nghiem Diep, Tan Ngoc Pham, Tri Cao, Binh Nguyen, Paul Swoboda, Nhat Ho, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag, Mathias Niepert
Optimality of Message-Passing Architectures for Sparse Graphs	here	Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings	here	Ningyi Liao, Siqiang Luo, Xiang Li, Jieming Shi
A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking	here	Hao Yan, Chaozhuo Li, Ruosong Long, Chao Yan, Jianan Zhao, Wenwen Zhuang, Jun Yin, Peiyan Zhang, Weihao Han, Hao Sun, Weiwei Deng, Qi Zhang, Lichao Sun, Xing Xie, Senzhang Wang
Universal Prompt Tuning for Graph Neural Networks	here	Taoran Fang, Yunchao Zhang, YANG YANG, Chunping Wang, Lei Chen
PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis	here	Ali TehraniJamsaz, Quazi Ishtiaque Mahmud, Le Chen, Nesreen K. Ahmed, Ali Jannesari
Fair Graph Distillation	here	Qizhang Feng, Zhimeng Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, Xia Hu
D4Explainer: In-distribution Explanations of Graph Neural Network via Discrete Denoising Diffusion	here	Jialin Chen, Shirley Wu, Abhijit Gupta, Rex Ying
SAME: Uncovering GNN Black Box with Structure-aware Shapley-based Multipiece Explanations	here	Ziyuan Ye, Rihan Huang, Qilin Wu, Quanying Liu
Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications	here	Xinyu Ma, Xu Chu, Yasha Wang, Yang Lin, Junfeng Zhao, Liantao Ma, Wenwu Zhu
TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery	here	Jialin Chen, Rex Ying
Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization	here	Haonan Yuan, Qingyun Sun, Xingcheng Fu, Ziwei Zhang, Cheng Ji, Hao Peng, Jianxin Li
Expressivity-Preserving GNN Simulation	here	Fabian Jogl, Maximilian Thiessen, Thomas Gärtner
Practical Contextual Bandits with Feedback Graphs	here	Mengxiao Zhang, Yuheng Zhang, Olga Vrousgou, Haipeng Luo, Paul Mineiro
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets	here	Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron Courville, Yoshua Bengio, Ling Pan
MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data	here	Tianyu Liu, Yuge Wang, Rex Ying, Hongyu Zhao
Characterization and Learning of Causal Graphs with Small Conditioning Sets	here	Murat Kocaoglu
GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search	here	Xiao Zang, Miao Yin, Jinqi Xiao, Saman Zonouz, Bo Yuan
A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs	here	Zhaocheng Zhu, Xinyu Yuan, Michael Galkin, Louis-Pascal Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks	here	Kexin Huang, Ying Jin, Emmanuel Candes, Jure Leskovec
[Re] On Explainability of Graph Neural Networks via Subgraph Explorations	here	Yannik Mahlau, Lukas Berg, Leonie Kayser
NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics	here	Anwar Said, Roza Bayrak, Tyler Derr, Mudassir Shabbir, Daniel Moyer, Catie Chang, Xenofon Koutsoukos
WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding	here	Yanchao Tan, Zihao Zhou, Hang Lv, Weiming Liu, Carl Yang
Learning from Both Structural and Textual Knowledge for Inductive Knowledge Graph Completion	here	Kunxun Qi, Jianfeng Du, Hai Wan
Deep Insights into Noisy Pseudo Labeling on Graph Data	here	Botao WANG, Jia Li, Yang Liu, Jiashun Cheng, Yu Rong, Wenjia Wang, Fugee Tsung
Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data	here	Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song
On Class Distributions Induced by Nearest Neighbor Graphs for Node Classification of Tabular Data	here	Federico Errica
Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes	here	Cai Zhou, Xiyuan Wang, Muhan Zhang
Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning	here	Xiaojun Guo, Yifei Wang, Zeming Wei, Yisen Wang
Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power	here	Junru Zhou, Jiarui Feng, Xiyuan Wang, Muhan Zhang
Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs	here	Peng Jin, Yang Wu, Yanbo Fan, Zhongqian Sun, Wei Yang, Li Yuan
Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks	here	Xin Yan, Hui Fang, Qiang He
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning	here	Zhou Zhiyao, Sheng Zhou, Bochao Mao, Xuanyi Zhou, Jiawei Chen, Qiaoyu Tan, Daochen Zha, Yan Feng, Chun Chen, Can Wang
Accelerating Molecular Graph Neural Networks via Knowledge Distillation	here	Filip Ekström Kelvinius, Dimitar Georgiev, Artur Toshev, Johannes Gasteiger
Approximately Equivariant Graph Networks	here	Ningyuan Huang, Ron Levie, Soledad Villar
(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More	here	Jan Schuchardt, Yan Scholten, Stephan Günnemann
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond	here	Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions	here	Lukas Gosch, Simon Markus Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
Graph Clustering with Graph Neural Networks	nan	Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller
A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning	here	Yiyou Sun, Zhenmei Shi, Yixuan Li
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference	here	Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding
Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction	here	Tianyu Liu, Qitan Lv, Jie Wang, Shuling Yang, Hanzhu Chen
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks	here	Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park
Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman	here	Jiarui Feng, Lecheng Kong, Hao Liu, Dacheng Tao, Fuhai Li, Muhan Zhang, Yixin Chen
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network	here	Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang
GALOPA: Graph Transport Learning with Optimal Plan Alignment	here	Yejiang Wang, Yuhai Zhao, Daniel Zhengkui Wang, Ling Li
UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction	here	Yansong Ning, Hao Liu, Hao Wang, Zhenyu Zeng, Hui Xiong
Learning Nonparametric Latent Causal Graphs with Unknown Interventions	here	Yibo Jiang, Bryon Aragam
Learning Large Graph Property Prediction via Graph Segment Training	here	Kaidi Cao, Mangpo Phothilimtha, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi
TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs	here	Mangpo Phothilimtha, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Michael Burrows, Charith Mendis, Bryan Perozzi
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?	here	Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
Fine-grained Expressivity of Graph Neural Networks	here	Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris
On the Minimax Regret for Online Learning with Feedback Graphs	here	Khaled Eldowa, Emmanuel Esposito, Tom Cesari, Nicolò Cesa-Bianchi
Temporal Graph Benchmark for Machine Learning on Temporal Graphs	here	Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis	here	Abhinav Nippani, Dongyue Li, Haotian Ju, Haris Koutsopoulos, Hongyang Zhang
Evaluating Self-Supervised Learning for Molecular Graph Embeddings	here	Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu
GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection	here	Namyong Park, Ryan Rossi, Xing Wang, Antoine Simoulin, Nesreen K. Ahmed, Christos Faloutsos
GSLB: The Graph Structure Learning Benchmark	here	Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Yu
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection	here	Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization	here	Zhiqing Sun, Yiming Yang
Generalised f-Mean Aggregation for Graph Neural Networks	here	Ryan Kortvelesy, Steven D Morad, Amanda Prorok
Towards Label Position Bias in Graph Neural Networks	here	Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu Aggarwal, Jiliang Tang
Faster approximate subgraph counts with privacy	here	Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan, Anil Vullikanti
Does Invariant Graph Learning via Environment Augmentation Learn Invariance?	here	Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
Newton–Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems	here	Lingbing Guo, Weiqing Wang, Zhuo Chen, Ningyu Zhang, Zequn Sun, Yixuan Lai, Qiang Zhang, Huajun Chen
Outlier-Robust Gromov-Wasserstein for Graph Data	here	Lemin Kong, Jiajin Li, Jianheng Tang, Anthony Man-Cho So
Recurrent Temporal Revision Graph Networks	here	Yizhou Chen, Anxiang Zeng, Qingtao Yu, Kerui Zhang, Cao Yuanpeng, Kangle Wu, Guangda Huzhang, Han Yu, Zhiming Zhou
Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs	here	Yeyuan Chen, Dingmin Wang
A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs	here	Xingyue Huang, Miguel Romero, Ismail Ceylan, Pablo Barceló
Fragment-based Pretraining and Finetuning on Molecular Graphs	here	Kha-Dinh Luong, Ambuj K Singh
Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics	here	Liming Wu, Zhichao Hou, Jirui Yuan, Yu Rong, Wenbing Huang
Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions	here	Duligur Ibeling, Thomas Icard
Graph Contrastive Learning with Stable and Scalable Spectral Encoding	here	Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi
Graph Convolutional Kernel Machine versus Graph Convolutional Networks	here	Zhihao Wu, Zhao Zhang, Jicong Fan
Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection	here	Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Ozgur, Olgica Milenkovic
Latent Graph Inference with Limited Supervision	here	Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, Yun Fu
A Fractional Graph Laplacian Approach to Oversmoothing	here	Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach	here	Nurendra Choudhary, Nikhil Rao, Chandan Reddy
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings	here	John Falk, Luigi Bonati, Pietro Novelli, Michele Parrinello, Massimiliano Pontil
Data-Centric Learning from Unlabeled Graphs with Diffusion Model	here	Gang Liu, Eric Inae, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang
Zero-One Laws of Graph Neural Networks	here	Sam Adam-Day, Iliant, Ismail Ceylan
CAT-Walk: Inductive Hypergraph Learning via Set Walks	here	Ali Behrouz, Farnoosh Hashemi, Sadaf Sadeghian, Margo Seltzer
Bayesian Optimisation of Functions on Graphs	here	Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A Osborne, Xiaowen Dong
Affinity-Aware Graph Networks	here	Ameya Velingker, Ali Sinop, Ira Ktena, Petar Veličković, Sreenivas Gollapudi
Reversible and irreversible bracket-based dynamics for deep graph neural networks	here	Anthony Gruber, Kookjin Lee, Nathaniel Trask
V-InFoR: A Robust Graph Neural Networks Explainer for Structurally Corrupted Graphs	here	Senzhang Wang, Jun Yin, Chaozhuo Li, Xing Xie, Jianxin Wang
The Graph Pencil Method: Mapping Subgraph Densities to Stochastic Block Models	here	Lee Gunderson, Gecia Bravo-Hermsdorff, Peter Orbanz
Towards Better Dynamic Graph Learning: New Architecture and Unified Library	here	Le Yu, Leilei Sun, Bowen Du, Weifeng Lv
Quasi-Monte Carlo Graph Random Features	here	Isaac Reid, Adrian Weller, Krzysztof M Choromanski
GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning	here	Haiteng Zhao, Shengchao Liu, Ma Chang, Hannan Xu, Jie Fu, Zhihong Deng, Lingpeng Kong, Qi Liu
Interpretable Graph Networks Formulate Universal Algebra Conjectures	here	Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Lupidi, Lucie Charlotte Magister, Pietro Lió, Pietro Barbiero
Neural Graph Generation from Graph Statistics	here	Kiarash Zahirnia, Yaochen Hu, Mark Coates, Oliver Schulte
Towards Self-Interpretable Graph-Level Anomaly Detection	here	Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan
CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graphs	here	Guangyao Zhai, Evin Pınar Örnek, Shun-Cheng Wu, Yan Di, Federico Tombari, Nassir Navab, Benjamin Busam
Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis	here	Junfeng Fang, Wei Liu, Yuan Gao, Zemin Liu, An Zhang, Xiang Wang, Xiangnan He
Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks	here	Jun Yin, Chaozhuo Li, Hao Yan, Jianxun Lian, Senzhang Wang
TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph	here	Xueyuan Lin, Haihong E, Chengjin Xu, Gengxian Zhou, Haoran Luo, Tianyi Hu, Fenglong Su, Ningyuan Li, Mingzhi Sun
PRODIGY: Enabling In-context Learning Over Graphs	here	Qian Huang, Hongyu Ren, Peng Chen, Gregor Kržmanc, Daniel Zeng, Percy Liang, Jure Leskovec
Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective	here	Zihan Luo, Hong Huang, Jianxun Lian, Xiran Song, Xing Xie, Hai Jin
Imagine That! Abstract-to-Intricate Text-to-Image Synthesis with Scene Graph Hallucination Diffusion	here	Shengqiong Wu, Hao Fei, Hanwang Zhang, Tat-Seng Chua
GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph	here	Xin Li, Dongze Lian, Zhihe Lu, Jiawang Bai, Zhibo Chen, Xinchao Wang
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization	here	Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji
Taming Local Effects in Graph-based Spatiotemporal Forecasting	here	Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi
From Trainable Negative Depth to Edge Heterophily in Graphs	here	Yuchen Yan, Yuzhong Chen, Huiyuan Chen, Minghua Xu, Mahashweta Das, Hao Yang, Hanghang Tong
Graph of Circuits with GNN for Exploring the Optimal Design Space	here	Aditya Shahane, Saripilli Swapna Manjiri, Ankesh Jain, Sandeep Kumar
Self-supervised Graph Neural Networks via Low-Rank Decomposition	here	Liang Yang, Runjie Shi, Qiuliang Zhang, bingxin niu, Zhen Wang, Xiaochun Cao, Chuan Wang
Certifiably Robust Graph Contrastive Learning	here	Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang
Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection	here	Hezhe Qiao, Guansong Pang
Efficient Learning of Linear Graph Neural Networks via Node Subsampling	here	Seiyun Shin, Ilan Shomorony, Han Zhao
Graph Denoising Diffusion for Inverse Protein Folding	here	Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang
PlanE: Representation Learning over Planar Graphs	here	Radoslav Dimitrov, Zeyang Zhao, Ralph Abboud, Ismail Ceylan
A Metadata-Driven Approach to Understand Graph Neural Networks	here	Ting Wei Li, Qiaozhu Mei, Jiaqi Ma
Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks	here	Jiarong Xu, Renhong Huang, XIN JIANG, Yuxuan Cao, Carl Yang, Chunping Wang, YANG YANG
Language Semantic Graph Guided Data-Efficient Learning	here	Wenxuan Ma, Shuang Li, lincan Cai, Jingxuan Kang
The expressive power of pooling in Graph Neural Networks	here	Filippo Maria Bianchi, Veronica Lachi
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach	here	Kai Zhao, Qiyu Kang, Yang Song, Rui She, Sijie Wang, Wee Peng Tay
Learning Invariant Representations of Graph Neural Networks via Cluster Generalization	here	Donglin Xia, Xiao Wang, Nian Liu, Chuan Shi
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift	here	Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He
LogSpecT: Feasible Graph Learning Model from Stationary Signals with Recovery Guarantees	here	Shangyuan LIU, Linglingzhi Zhu, Anthony Man-Cho So
Simplifying and Empowering Transformers for Large-Graph Representations	here	Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan
Interpretable Prototype-based Graph Information Bottleneck	here	Sangwoo Seo, Sungwon Kim, Chanyoung Park
A new perspective on building efficient and expressive 3D equivariant graph neural networks	here	weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla Gomes, Zhi-Ming Ma
On the Ability of Graph Neural Networks to Model Interactions Between Vertices	here	Noam Razin, Tom Verbin, Nadav Cohen
Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge	here	Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu
Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints	here	Jiaxin Bai, Xin Liu, Weiqi Wang, Chen Luo, Yangqiu Song
Multi-task Graph Neural Architecture Search with Task-aware Collaboration and Curriculum	here	Yijian Qin, Xin Wang, Ziwei Zhang, Hong Chen, Wenwu Zhu
Lovász Principle for Unsupervised Graph Representation Learning	here	Ziheng Sun, Chris Ding, Jicong Fan
Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts	here	Zeyang Zhang, Xin Wang, Ziwei Zhang, Zhou Qin, Weigao Wen, Hui Xue', Haoyang Li, Wenwu Zhu
Optimizing over trained GNNs via symmetry breaking	here	Shiqiang Zhang, Juan Campos, Christian Feldmann, David Walz, Frederik Sandfort, Miriam Mathea, Calvin Tsay, Ruth Misener
Tailoring Self-Attention for Graph via Rooted Subtrees	here	Siyuan Huang, Yunchong Song, Jiayue Zhou, Zhouhan Lin
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks	here	Vignesh Kothapalli, Tom Tirer, Joan Bruna
On Learning Necessary and Sufficient Causal Graphs	here	Hengrui Cai, Yixin Wang, Michael Jordan, Rui Song
When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability	here	Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup
Limits, approximation and size transferability for GNNs on sparse graphs via graphops	here	Thien Le, Stefanie Jegelka
SPA: A Graph Spectral Alignment Perspective for Domain Adaptation	here	Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao
Intervention Generalization: A View from Factor Graph Models	here	Gecia Bravo-Hermsdorff, David Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva
Transformers over Directed Acyclic Graphs	here	Yuankai Luo, Veronika Thost, Lei Shi
Fast Approximation of Similarity Graphs with Kernel Density Estimation	here	Peter Macgregor, He Sun
Graph-Structured Gaussian Processes for Transferable Graph Learning	here	Jun Wu, Lisa Ainsworth, Andrew Leakey, Haixun Wang, Jingrui He
Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data	here	Saptarshi Roy, Raymond K. W. Wong, Yang Ni
Penguin: Parallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference	here	Ran Ran, Nuo Xu, Tao Liu, Wei Wang, Gang Quan, Wujie Wen
High dimensional, tabular deep learning with an auxiliary knowledge graph	here	Camilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec
4D Panoptic Scene Graph Generation	here	Jingkang Yang, Jun CEN, WENXUAN PENG, Shuai Liu, Fangzhou Hong, Xiangtai Li, Kaiyang Zhou, Qifeng Chen, Ziwei Liu
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling	here	Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Kompella, Zhangyang "Atlas" Wang
Demystifying Oversmoothing in Attention-Based Graph Neural Networks	here	Xinyi Wu, Amir Ajorlou, Zihui Wu, Ali Jadbabaie
Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective	here	Yifei Zhang, Hao Zhu, yankai Chen, Zixing Song, Piotr Koniusz, Irwin King
Geometric Analysis of Matrix Sensing over Graphs	here	Haixiang Zhang, Ying Chen, Javad Lavaei
GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation	here	Mingxuan Ju, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence	here	Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada
SyncTREE: Fast Timing Analysis for Integrated Circuit Design through a Physics-informed Tree-based Graph Neural Network	here	Yuting Hu, Jiajie Li, Florian Klemme, Gi-Joon Nam, Tengfei Ma, Hussam Amrouch, Jinjun Xiong
Variational Annealing on Graphs for Combinatorial Optimization	here	Sebastian Sanokowski, Wilhelm Berghammer, Sepp Hochreiter, Sebastian Lehner
Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs	here	CHEN SHENGYUAN, Yunfeng Cai, Huang Fang, Xiao Huang, Mingming Sun
Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily	here	Langzhang Liang, Xiangjing Hu, Zenglin Xu, Zixing Song, Irwin King
No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning	here	Zixing Song, Yifei Zhang, Irwin King
Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning	here	Zixing Song, Yifei Zhang, Irwin King
Simple and Asymmetric Graph Contrastive Learning without Augmentations	here	Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang
Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems	here	Fiona Lippert, Bart Kranstauber, Emiel van Loon, Patrick Forré
An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations	here	Haoran Yang, Xiangyu Zhao, Yicong Li, Hongxu Chen, Guandong Xu
Provable Training for Graph Contrastive Learning	here	Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi
FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective	here	Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu
Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First	here	Zheng Zhang, Junxiang Wang, Liang Zhao
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules	here	ZHIYUAN LIU, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua
Video-Mined Task Graphs for Keystep Recognition in Instructional Videos	here	Kumar Ashutosh, Santhosh Kumar Ramakrishnan, Triantafyllos Afouras, Kristen Grauman
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts	here	Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova
Joint Feature and Differentiable $ k $-NN Graph Learning using Dirichlet Energy	here	Lei Xu, Lei Chen, Rong Wang, Feiping Nie, Xuelong Li
Directional diffusion models for graph representation learning	here	Run Yang, Yuling Yang, Fan Zhou, Qiang Sun
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks	here	Yuhang Yao, Weizhao Jin, Srivatsan Ravi, Carlee Joe-Wong
Unsupervised Graph Neural Architecture Search with Disentangled Self-Supervision	here	Zeyang Zhang, Xin Wang, Ziwei Zhang, Guangyao Shen, Shiqi Shen, Wenwu Zhu
Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion	here	Hyuna Cho, Minjae Jeong, Sooyeon Jeon, Sungsoo Ahn, Won Hwa Kim
[Re] $\mathcal{G}$-Mixup: Graph Data Augmentation for Graph Classification	here	Ermin Omeragic, Vuk Đuranović
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking	here	Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
Sparse Graph Learning from Spatiotemporal Time Series	nan	Andrea Cini, Daniele Zambon, Cesare Alippi
What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding	here	Nicolas Keriven, Samuel Vaiter
Sheaf Hypergraph Networks	here	Iulia Duta, Giulia Cassarà, Fabrizio Silvestri, Pietro Lió
A graphon-signal analysis of graph neural networks	here	Ron Levie
MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy	here	Honghua Dong, Jiawei Xu, Yu Yang, Rui Zhao, Shiwen Wu, Chun Yuan, Xiu Li, Chris Maddison, Lei Han
Curvature Filtrations for Graph Generative Model Evaluation	here	Joshua Southern, Jeremy Wayland, Michael Bronstein, Bastian Rieck
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals	here	Tingting Dan, Jiaqi Ding, Ziquan Wei, Shahar Kovalsky, Minjeong Kim, Won Hwa Kim, Guorong Wu
Large sample spectral analysis of graph-based multi-manifold clustering	nan	Nicolas Garcia Trillos, Pengfei He, Chenghui Li
Network Regression with Graph Laplacians	nan	Yidong Zhou, Hans-Georg Müller