hongjinwu Goto Github PK

book-mathmatical-foundation-of-reinforcement-learning

This is the homepage of a new book entitled "Mathmatical Foundations of Reinforcement Learning."

d-gex

Deep learning for gene expression inference

deepvariant

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

gcng

using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions

gnnpapers

Must-read papers on graph neural networks (GNN)

graph-representation-learning-tutorial

Code for Data61's tutorial on Graph Representation Learning

graphsage-pytorch

A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.

graphsage-simple

Simple reference implementation of GraphSAGE.

hello-world

test

molecular-vae

Implementation of the paper - Automatic chemical design using a data-driven continuous representation of molecules

neural-fingerprint

Convolutional nets which can take molecular graphs of arbitrary size as input.

ngs-analysis

二代测序数据分析

organ

Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models

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.

progen

Official release of the ProGen models

protein-bert-pytorch

Implementation of ProteinBERT in Pytorch

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

reinvent

Molecular De Novo design using Recurrent Neural Networks and Reinforcement Learning

sharebooks

ShareBooks

sprint_gan

Privacy-preserving generative deep neural networks support clinical data sharing

wae

Wasserstein Auto-Encoders

wassersteingan