- Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks
- Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem
- Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels
- Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation
- ComGA: Community-Aware Attributed Graph Anomaly Detection
- Linear, or Non-Linear, That is the Question!
- Profiling the Design Space for Graph Neural Networks based Collaborative Filtering
- Graph Collaborative Reasoning
- Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation
- Geometric Inductive Matrix Completion: A Hyperbolic Approach with Unified Message Passing
- Learning Multi-granularity Consecutive User Intent Unit for Session-based Recommendation
- Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation
- HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling
- Outside In: Market-aware Heterogeneous Graph Neural Network for Employee Turnover Prediction
- Interpretable Relation Learning on Heterogeneous Graphs
- Community Trend Prediction on Heterogeneous Graph in E-commerce
- EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning over Temporal Knowledge Graphs
- Diversified Query Generation Guided by Knowledge Graph
- A Neighborhood-Attention Fine-grained Entity Typing for Knowledge Graph Completion
- Informed Multi-context Entity Alignment
- Multi-Scale Variational Graph AutoEncoder for Link Prediction
- Learning Concept Prerequisite Relations from Educational Data via Multi-Head Attention Variational Graph Auto-Encoders
- A GNN-based Multi-task Learning Framework for Personalized Video Search
- Joint Learning of E-commerce Search and Recommendation with a Unified Graph Neural Network
- Triangle Graph Interest Network for Click-through Rate Prediction
- Ada-GNN: Adapting to Local Patterns for Improving Graph Neural Networks
- Efficient Graph Convolution for Joint Node Representation Learning and Clustering
- KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification
- Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations
- Learning Fair Node Representations with Graph Counterfactual Fairness
- Harvesting More Answer Spans from Paragraph beyond Annotation
- Predicting Human Mobility via Graph Convolutional Dual-attentive Networks
- Friend Story Ranking with Edge-Contextual Local Graph Convolutions