Stars
FAIR Chemistry's library of machine learning methods for chemistry
Run multiple AI models against the same research, design, or coding task. Surface disagreements before you ship.
Automated bonded parameters for Martini 3
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery (EMNLP'24)
My tools for the Torque resource manager
Data for DeePMD-kit v2 paper
A deep learning package for many-body potential energy representation and molecular dynamics
A unified interface for optimization algorithms and experiments
UF3: a python library for generating ultra-fast interatomic potentials
The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
NequIP is a code for building E(3)-equivariant interatomic potentials
Easily generate flowcharts and diagrams from text ⿻
ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.
An open source python library for scalable Bayesian optimisation.
Bayesian optimisation & Reinforcement Learning library developed by Huawei Noah's Ark Lab
Python Toolkit for Causal and Probabilistic Reasoning
An Open Source Machine Learning Framework for Everyone
JAX-ReaxFF: A Gradient Based Framework for Extremely Fast Optimization of Reactive Force Fields
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Differentiable, Hardware Accelerated, Molecular Dynamics
Source code for the X Recommendation Algorithm
(NeurIPS 2022) Official Implementation of "Preservation of the Global Knowledge by Not-True Distillation in Federated Learning"
FedMD: Heterogenous Federated Learning via Model Distillation