force-fields topic

Build neural networks for machine learning force fields with JAX

thorben-frank

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

CederGroupHub

List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning

AspirinCode

[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

atomicarchitects

[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

atomicarchitects

KIM-based Learning-Integrated Fitting Framework for interatomic potentials.

openkim

MACE-MP models

ACEsuit

[ArXiv 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields

atomicarchitects