Hongjin Wu's repositories
papers_for_protein_design_using_DL
List of papers about Proteins Design using Deep Learning
PINNpapers
Must-read Papers on Physics-Informed Neural Networks.
pinns-torch
PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.
deeplearning-biology
A list of deep learning implementations in biology
Book-Mathmatical-Foundation-of-Reinforcement-Learning
This is the homepage of a new book entitled "Mathmatical Foundations of Reinforcement Learning."
progen
Official release of the ProGen models
GNNPapers
Must-read papers on graph neural networks (GNN)
ShareBooks
ShareBooks
graphSAGE-pytorch
A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.
deepvariant
DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
Graph-Representation-Learning-Tutorial
Code for Data61's tutorial on Graph Representation Learning
ORGAN
Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models
protein-bert-pytorch
Implementation of ProteinBERT in Pytorch
REINVENT
Molecular De Novo design using Recurrent Neural Networks and Reinforcement Learning
GCNG
using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions
molecular-VAE
Implementation of the paper - Automatic chemical design using a data-driven continuous representation of molecules
NGS-analysis
二代测序数据分析
pytorch-handbook
pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
graphsage-simple
Simple reference implementation of GraphSAGE.
hello-world
test
SPRINT_gan
Privacy-preserving generative deep neural networks support clinical data sharing
D-GEX
Deep learning for gene expression inference
wae
Wasserstein Auto-Encoders
DLforGenomics
Review Paper: Deep Learning for Genomics: A Concise Overview
neural-fingerprint
Convolutional nets which can take molecular graphs of arbitrary size as input.