CuspAI/kUPS-mattersim-jax

MACE-MH-1 is a foundation machine-learning interatomic potential (MLIP) that bridges molecular, surface, and materials chemistry through cross-domain learning:

UBio-MolFM is a foundation-model suite for molecular modeling, designed for bio-systems. This release, UBio-MolFM-V1.5 (Stage 3), is built on the E2Former-V2 linear-scaling equivariant transformer and is the checkpoint used for every simulation reported in UBio-MolFM: Enabling Biomolecular Dynamics…

Another list focuses on Python stuff related to Chemistry.

E(3)-equivariant neural network interatomic potentials achieving DFT accuracy with up to 1000× less training data than invariant models, foundational architecture behind MACE and Allegro (Harvard, MIT, Nature Communications 2022)

Deep learning atomistic model across elements, temperatures, and pressures

Highly scalable equivariant deep learning interatomic potentials enabling million-atom molecular dynamics simulations with ab initio accuracy, building on E(3)-equivariant architectures for large-scale atomistic modeling (mir-group, MIT License, 480+ stars)