randyriemann

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

GraphEmbedding

Implementation and experiments of graph embedding algorithms.

Graphormer

Graphormer is a general-purpose deep learning backbone for molecular modeling.

score_sde_pytorch

PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

GraphGym

Platform for designing and evaluating Graph Neural Networks (GNN)

score_sde

Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

deepmd-kit

A deep learning package for many-body potential energy representation and molecular dynamics

powerful-gnns

How Powerful are Graph Neural Networks?

deep_gcns_torch

Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org

PaddleHelix

Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集

awesome-equivariant-network

Paper list for equivariant neural network

dgl-lifesci

Python package for graph neural networks in chemistry and biology

awesome-pretrain-on-molecules

[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models

torchani

Accurate Neural Network Potential on PyTorch

GraphINVENT

Graph neural networks for molecular design.

openff-toolkit

The Open Forcefield Toolkit provides implementations of the SMIRNOFF format, parameterization engine, and other tools. Documentation available at http://open-forcefield-toolkit.readthedocs.io

molecule-generation

Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation

NeuralForceField

Neural Network Force Field based on PyTorch

variational-inference-with-normalizing-flows

Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)

DiffuStereo

This repository is the official implementation of DiffuStereo: High Quality Human Reconstruction via Diffusion-based Stereo Using Sparse Cameras.

paper_boltzmann_generators

charge_transfer_nnp

Graph neural network potential with charge transfer

AutoForce

Sparse Gaussian Process Potentials

TCCL-Code

Code and scripts for theoretical and computational chemistry, developed in TCCL, Department of Chemistry, Tsinghua University. These scripts read the out put of ADF, CP2K, Dmol3, Gaussian, NWChem, Molpro program.

normalizing-flows

Normalizing flows with pytorch

compchem-scripts

A repository for the scripts that I find useful when dealing with computational chemistry data from gaussian/turbomole/tinker etc packages. Some scripts are a lot cleaner/more user friendly than others. I will try to fix them when I have some time

library-g09

Example of Gaussian input file for special case in computational chemistry project.

C343-Computational-Chemistry-Lab

Contains exercises for C343 Computational Lab. Quantum Calculations are done using Gaussian 9. Codes written in Python.