Chuan Shi

18

Papers

115

Total Citations

Papers (18)

FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization

Graph Invariant Learning with Subgraph Co-mixup for Out-of-Distribution Generalization

A Generalized Neural Diffusion Framework on Graphs

Graph Contrastive Invariant Learning from the Causal Perspective

Blend the Separated: Mixture of Synergistic Experts for Data-Scarcity Drug-Target Interaction Prediction

Federated Graph Condensation with Information Bottleneck Principles

Harnessing Language Model for Cross-Heterogeneity Graph Knowledge Transfer

Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective

Graph Distillation with Eigenbasis Matching

Less is More: on the Over-Globalizing Problem in Graph Transformers

Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration

Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum

Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure

Uncovering the Structural Fairness in Graph Contrastive Learning

Injecting Multimodal Information into Rigid Protein Docking via Bi-level Optimization

Graph Contrastive Learning with Stable and Scalable Spectral Encoding

Learning Invariant Representations of Graph Neural Networks via Cluster Generalization

Provable Training for Graph Contrastive Learning