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EPFL CH-457 "AI for chemistry"
Multimodal Transformer for Predicting Global Minimum Adsorption Energy
A unified platform for fine-tuning atomistic foundation models in chemistry and materials science
A python library for calculating materials properties from the PES
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
atomate2 is a library of computational materials science workflows
VIP cheatsheet for Stanford's CME 295 Transformers and Large Language Models
VIP cheatsheets for Stanford's CS 221 Artificial Intelligence
VIP cheatsheets for Stanford's CS 230 Deep Learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
Torch-native, batchable, atomistic simulation.
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
Generic template to bootstrap your PyTorch project.
SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
Semiempirical Extended Tight-Binding Program Package
Agent-based sequential learning software for materials discovery
p4vasp, the VASP Visualization Tool
FAIR Chemistry's library of machine learning methods for chemistry
Uniform Manifold Approximation with Two-phase Optimization (IEEE VIS 2022 short)
PyTorch Library for Active Learning to accompany Human-in-the-Loop Machine Learning book
This is the repository of the code and data needed for reproducing the results of the paper "Neural Network-Assisted Development of High-Entropy Alloy Catalysts: Decoupling Ligand and Coordination …
An automatic engine for predicting materials properties.
libAtoms/QUIP molecular dynamics framework: https://libatoms.github.io
96 benchmark datasets for external clustering validation with class-label matching score
The implementation of between dataset internal measures