Stars
Material structure processing software based on ASE (Atomic Simulation Environment)
A python library for calculating materials properties from the PES
A module for ASE for elastic constants calculation.
MACE foundation models (MP, OMAT, Matpes)
FacTool: Factuality Detection in Generative AI
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
GPTFF allowing anyone to directly download and run the AI model in an out-of-the-box manner
Safe RLHF: Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback
Code for LAMOL: LAnguage MOdeling for Lifelong Language Learning
Generative Agents: Interactive Simulacra of Human Behavior
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
Create Customized Software using Natural Language Idea (through LLM-powered Multi-Agent Collaboration)
Exchange-of-Thought: Enhancing Large Language Model Capabilities through Cross-Model Communication
FrugalGPT: better quality and lower cost for LLM applications
The official sources for the RDKit library
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning …
torch-molecule is a deep learning package for molecular discovery, designed with an sklearn-style interface for property prediction, inverse design and representation learning.
kskjs1203 / SevenNet-reEWC
Forked from MDIL-SNU/SevenNetSevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.
Equivariant Graph Neural Networks for Atomic Charge Prediction
A Python implementation of global optimization with gaussian processes.
A Python software package for saddle point optimization and minimization of atomic systems.
A web-based collaborative LaTeX editor
Benchmark Suite for Machine Learning Interatomic Potentials for Materials
Repository for data and figure generation used in "Distillation of atomistic foundation models across architectures and chemical domains"