Pinned Repositories
autoLiterature
autoLiterature是一个基于Dropbox和Python的自动文献管理器。
deepsnap
Python library assists deep learning on graphs
DrugBAN
Interpretable bilinear attention network with domain adaptation improves drug-target prediction.
drugVQA
Predicting Drug Protein Interaction using Quasi-Visual Question Answering System
GraphGym
Platform for designing and evaluating Graph Neural Networks (GNN)
GripNet
Graph Representation Learning and Interpreting via Multi-graph Information Propagation (In submission, 2020)
MapDiff
Implementation of MapDiff: "Mask prior-guided denoising diffusion improves inverse protein folding" in PyTorch
TDC
Therapeutics Data Commons: Machine Learning Datasets for Therapeutics
pykale
Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem. ⭐ Star to support our work!
shef-ai.github.io
Web site for the Sheffield Data Science and AI Community
peizhenbai's Repositories
peizhenbai/DrugBAN
Interpretable bilinear attention network with domain adaptation improves drug-target prediction.
peizhenbai/MapDiff
Implementation of MapDiff: "Mask prior-guided denoising diffusion improves inverse protein folding" in PyTorch
peizhenbai/autoLiterature
autoLiterature是一个基于Dropbox和Python的自动文献管理器。
peizhenbai/deepsnap
Python library assists deep learning on graphs
peizhenbai/drugVQA
Predicting Drug Protein Interaction using Quasi-Visual Question Answering System
peizhenbai/gcmc
Re-Implement "Graph Convolutional Matrix Completion" (PyTorch and PyTorch Geometric)
peizhenbai/GraphDTA
GraphDTA: Predicting drug-target binding affinity with graph neural networks
peizhenbai/GraphGym
Platform for designing and evaluating Graph Neural Networks (GNN)
peizhenbai/GripNet
Graph Representation Learning and Interpreting via Multi-graph Information Propagation (In submission, 2020)
peizhenbai/MolCLR
Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.
peizhenbai/pykale
Knowledge-aware machine learning for medical imaging, graph analysis, and computer vision. KALE stands for Knowledge-Aware LEarning.
peizhenbai/TDC
Therapeutics Data Commons: Machine Learning Datasets for Therapeutics
peizhenbai/SEAL
SEAL (learning from Subgraphs, Embeddings, and Attributes for Link prediction). "M. Zhang, Y. Chen, Link Prediction Based on Graph Neural Networks, NeurIPS 2018 spotlight".
peizhenbai/SEAL_OGB
An open-source implementation of SEAL for link prediction in open graph benchmark (OGB) datasets.