Lirong Wu

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

LirongWu

Awesome Protein Representation Learning

LirongWu

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

LirongWu

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

LirongWu

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

LirongWu

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"

LirongWu

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

LirongWu

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

LirongWu

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

LirongWu

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

LirongWu