README.md

Publications in ICDM 2023

Interpretability

• Interpretable Subgraph Feature Extraction for Hyperlink Prediction
• Toward Interpretable Graph Neural Networks via Concept Matching Model
• Limitations of Perturbation-based Explanation Methods for Temporal Graph Neural Networks

Time Series

• Rethinking Temporal Dependencies in Multiple Time Series: A Use Case in Financial Data
• MTT-DynGL: Towards Multidimensional Topology-oriented Time-series Dynamic Graphs Learning Model

Temporal Knowledge Graphs

• IE-Evo: Internal and External Evolution-Enhanced Temporal Knowledge Graph Forecasting
• Homogeneous Entity Context Enhanced Representation Network for Temporal Knowledge Graph Reasoning

Alignment

• Efficient and Effective Entity Alignment for Evolving Temporal Knowledge Graphs
• Robust Network Alignment with the Combination of Structure and Attribute Embeddings

SpatioTemporal Data

• Boosting Urban Prediction via Addressing Spatial-Temporal Distribution Shift
• Meteorology-Assisted Spatio-Temporal Graph Network for Uncivilized Urban Event Prediction
• Early Spatiotemporal Event Prediction via Adaptive Controller and Spatiotemporal Embedding

Traffic Forecasting

• Spatio-Temporal Hypergraph Neural ODE Network for Traffic Forecasting
• STSD: Modeling Spatial Temporal Staticity and Dynamicity in Traffic Forecasting

Missing Data

• Towards Unsupervised Graph Completion Learning on Graphs with Features and Structure Missing
• Uncertainty-aware Traffic Prediction under Missing Data

Disease

• RDKG: A Reinforcement Learning Framework for Disease Diagnosis on Knowledge Graph
• Enhancing Personalized Healthcare via Capturing Disease Severity, Interaction, and Progression
• Discovering Protein Interactions and Repurposing Drugs in SARS-CoV-2 (COVID-19) via Learning on Robust Multipartite Graphs

Data Augmentation

• GMMDA: Gaussian Mixture Modeling of Graph in Latent Space for Graph Data Augmentation
• Pseudo-Labeling with Graph Active Learning for Few-shot Node Classification

Scalability

• Context Sketching for Memory-efficient Graph Representation Learning
• MPGraf: a Modular and Pre-trained Graphformer for Learning to Rank at Web-scale
• Double Wins: Boosting Accuracy and Efficiency of Graph Neural Networks by Reliable Knowledge Distillation

Distributed Learning

• Entropy Aware Training for Fast and Accurate Distributed GNN
• Unfairness in Distributed Graph Frameworks

Federated Learning

• Federated Learning for Privacy-Preserving Prediction of Occupational Group Mobility Using Multi-Source Mobile Data
• Equipping Federated Graph Neural Networks with Structure-aware Group Fairness

Fairness

• Graph Sampling based Fairness-aware Recommendation over Sensitive Attribute Removal
• Mitigating Multisource Biases in Graph Neural Networks via Real Counterfactual Samples

Collaborative Filtering

• Enhancing Graph Collaborative Filtering via Neighborhood Structure Embedding
• Graph Neural Ordinary Differential Equations-based method for Collaborative Filtering

Recommendation

• Auto Graph Filtering for Bundle Recommendation
• Variational Collective Graph AutoEncoder for Multi-behavior Recommendation
• MCRec: Multi-channel Gated Gifts Recommendation
• Collaborative Word-based Pre-trained Item Representation for Transferable Recommendation
• Graph Collaborative Optimization for Sequential Recommendation

Sesssion-based Recommendation

• FM-IGNN: Interaction Graph Neural Network with Fine-grained Matching for Session-based Recommendation
• Session-based Interactive Recommendation via Deep Reinforcement Learning``

Hypergraphs for Recommendation

• Bilateral Sequential Hypergraph Convolution Network for Reciprocal Recommendation
• Hypergraph Attribute Attention Network for Community Recommendation

Knowledge Graphs for Recommendation

• IKGN: Intention-aware Knowledge Graph Network for POI Recommendation
• PKAT: Pre-training in Collaborative Knowledge Graph Attention Network for Recommendation

Heterogenous Graphs

• A Graph Convolutional Neural Network for Recommendation Based on Community Detection and Combination of Multiple Heterogeneous Graphs
• Self-supervised Heterogeneous Hypergraph Learning with Context-aware Pooling for Graph-level Classification

Contrastive Learning

• Contrastive Learning-based Multi-behavior Recommendation with Semantic Knowledge Enhancement
• Graph Self-Contrast Representation Learning
• DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing
• Hierarchical Graph Contrastive Learning via Debiasing Noise Samples with Adaptive Repelling Ratio
• Hypergraph Contrastive Learning for Drug Trafficking Community Detection

Graph Condensation

• CaT: Balanced Continual Graph Learning with Graph Condensation
• Two-Level Graph Representation Learning with Community-as-a-Node Graphs

Graph Anomaly Detection

• Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection
• PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection

Fraud Detection

• Enhancing GNN-based Fraud Detector via Semantic Extraction and Max-Representation-Margin
• Telecom Fraud Detection Based on Feature Binning and Autoencoder

Miscellaneous

• Infinitely Deep Graph Transformation Networks
• Multi-Hop Correlation Preserving Hashing for Efficient Hamming Space Retrieval
• Decision-focused Graph Neural Networks for Graph Learning and Optimization
• PatSTEG: Modeling Formation Dynamics of Patent Citation Networks via The Semantic-Topological Evolutionary Graph
• On the Verification of Embeddings with Hybrid Markov Logic
• To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data
• Graph Reciprocal Neural Networks by Abstracting Node as Attribute
• Graph Open-Set Recognition via Entropy Message Passing
• Dimensionality and Curvature Selection of Graph Embedding using Decomposed Normalized Maximum Likelihood Code-Length