Code for AAAI 2024 paper "PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction"

Code fo CIKM2024 paper "Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation"

Code for TNNLS paper "Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting"

Code for AAAI 2025 paper "Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization"

Awesome Protein Representation Learning

Code for ICML 2024 paper "Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning"

Code for TKDE paper "Self-supervised learning on graphs: Contrastive, generative, or predictive"

Code for TKDE paper "A Teacher-Free Graph Knowledge Distillation Framework with Dual Self-Distillation"

Code for AAAI 2023 (Oral) paper "Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effective GNN-to-MLP Distillation Framework"

Code for ICLR 2024 (Spotlight) paper "MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding"

Code for ECML-PKDD 2023 paper "Learning to Augment Graph Structure for both Homophily and Heterophily Graphs"

Code for TNNLS paper "Beyond Homophily and Homogeneity Assumption: Relation-based Frequency Adaptive Graph Neural Networks"

Code for TNNLS paper "Homophily-Enhanced Self-supervision for Graph Structure Learning: Insights and Directions"

Code for NeurIPS 2022 paper "Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks"

Code for ICML 2023 paper "Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs"

Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction"

Code for TNNLS paper "Deep Clustering and Visualization for End-to-End High Dimensional Data analysis"

Code for NCAA paper "Multi-level Disentanglement Graph Neural Network"

Code for WACV 2022 paper "Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation"