Alternatives and similar repositories for mess

Users that are interested in mess are comparing it to the libraries listed below

• lab-cosmo / jax-pme
  Particle-mesh based calculations of long-range interactions in JAX
  ☆23Updated this week
• ACEsuit / mace-jax
  Equivariant machine learning interatomic potentials in JAX.
  ☆83Updated this week
• Luthaf / vesin
  Compute neighbor lists for atomistic systems
  ☆73Updated this week
• mariogeiger / nequip-jax
  ☆23Updated 2 years ago
• tummfm / chemtrain
  Training Neural Network potentials through customizable routines in JAX.
  ☆62Updated 6 months ago
• lab-cosmo / torch-pme
  Particle-mesh based calculations of long-range interactions in PyTorch
  ☆70Updated last week
• felixmusil / torch_nl
  ☆19Updated 2 years ago
• balintmate / neural-thermodynamic-integration
  ☆12Updated 11 months ago
• ASK-Berkeley / StABlE-Training
  [TMLR 2025] Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators
  ☆15Updated 2 months ago
• mariogeiger / allegro-jax
  ☆22Updated 8 months ago
• jharrymoore / mace-md
  ☆17Updated last year
• vldgroup / graph-pes
  train and use graph-based ML models of potential energy surfaces
  ☆119Updated last month
• atomicarchitects / nequix
  [NeurIPS'25 AI4Mat] Nequix: Training a foundation model for materials on a budget and [arXiv'26] Phonon fine-tuning (PFT)
  ☆64Updated this week
• basf / mlipx
  Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…
  ☆96Updated last month
• metatensor / featomic
  Computing representations for atomistic machine learning
  ☆75Updated last week
• imagdau / aseMolec
  ☆32Updated 4 months ago
• thorben-frank / mlff
  Build neural networks for machine learning force fields with JAX
  ☆132Updated 8 months ago
• rubber-duck-debug / cuda-mace
  CUDA implementations of MACE models
  ☆23Updated 5 months ago
• metatensor / metatomic
  Atomistic machine learning models you can use everywhere for everything
  ☆33Updated last week
• ACEsuit / mace-tutorials
  Collection of tutorials to use the MACE machine learning force field.
  ☆51Updated 2 weeks ago
• graphcore-research / mess
  MESS: Modern Electronic Structure Simulations
  ☆20Updated last year
• tummfm / difftre
  Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting
  ☆36Updated last year
• atomind-ai / mlip-arena
  🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …
  ☆88Updated last week
• ASK-Berkeley / EScAIP
  [NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential
  ☆57Updated 4 months ago
• imagdau / Tutorials
  Collection of Tutorials on Machine Learning Interatomic Potentials
  ☆25Updated last year
• schwallergroup / lmkan
  ☆17Updated 4 months ago
• BIG-MAP / graph2mat
  graph2mat: Graph to matrix conversion
  ☆19Updated 2 weeks ago
• jla-gardner / load-atoms
  ⚛ download and manipulate atomistic datasets
  ☆48Updated 2 months ago
• microsoft / oneqmc
  Pretrained model for molecular wavefunctions
  ☆55Updated 2 weeks ago
• wcwitt / symmetrix
  ☆33Updated last week