Lirong Wu

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

awesome-protein-representation-learning. Awesome Protein Representation Learning

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

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

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

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

FF-G2M. 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"

Uni-Anti. Code fo ICLR2025 paper "A Simple yet Effective DDG Predictor is An Unsupervised Antibody Optimizer and Explainer"

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

Uni-Mol3. A PyTorch implementation of Uni-Mol3.

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

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

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

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

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

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

L2A. Code for ECML-PKDD 2023 paper "Learning to Augment Graph Structure for both Homophily and Heterophily Graphs"

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

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

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

lirongwu.github.io. HTML

LirongWu.

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