Alternatives and similar repositories for neural-thermodynamic-integration

Users that are interested in neural-thermodynamic-integration are comparing it to the libraries listed below

• ASK-Berkeley / StABlE-Training
  [TMLR 2025] Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators
  ☆15Updated 2 months ago
• lab-cosmo / torch-pme
  Particle-mesh based calculations of long-range interactions in PyTorch
  ☆70Updated last week
• lab-cosmo / jax-pme
  Particle-mesh based calculations of long-range interactions in JAX
  ☆23Updated this week
• hatemhelal / mess
  MESS: Modern Electronic Structure Simulations
  ☆43Updated 4 months ago
• vldgroup / graph-pes
  train and use graph-based ML models of potential energy surfaces
  ☆119Updated last month
• mariogeiger / nequip-jax
  ☆23Updated 2 years ago
• jharrymoore / mace-md
  ☆17Updated last year
• tummfm / chemtrain
  Training Neural Network potentials through customizable routines in JAX.
  ☆62Updated 6 months ago
• metatensor / metatomic
  Atomistic machine learning models you can use everywhere for everything
  ☆33Updated last week
• imagdau / Tutorials
  Collection of Tutorials on Machine Learning Interatomic Potentials
  ☆25Updated last year
• imagdau / aseMolec
  ☆32Updated 4 months ago
• Luthaf / vesin
  Compute neighbor lists for atomistic systems
  ☆73Updated this week
• duartegroup / mlp-train
  MLP training for molecular systems
  ☆55Updated 2 weeks ago
• ACEsuit / mace-off
  MACE-OFF23 models
  ☆59Updated last year
• ACEsuit / mace-jax
  Equivariant machine learning interatomic potentials in JAX.
  ☆83Updated this week
• ASK-Berkeley / MLFF-distill
  [ICLR 2025] Official Implementation of "Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy …
  ☆21Updated 9 months ago
• JoshRackers / equivariant_electron_density
  Generate and predict molecular electron densities with Euclidean Neural Networks
  ☆49Updated 2 years ago
• ChengUCB / les
  ☆41Updated last week
• ACEsuit / mace-tutorials
  Collection of tutorials to use the MACE machine learning force field.
  ☆51Updated 2 weeks ago
• metatensor / featomic
  Computing representations for atomistic machine learning
  ☆75Updated last week
• atomind-ai / mlip-arena
  🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …
  ☆88Updated last week
• schwallergroup / lmkan
  ☆17Updated 4 months ago
• ASK-Berkeley / EScAIP
  [NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential
  ☆57Updated 4 months ago
• basf / mlipx
  Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…
  ☆96Updated last month
• qiqb-osaka / mace-osaka24
  MACE_Osaka24 models
  ☆25Updated last year
• jla-gardner / load-atoms
  ⚛ download and manipulate atomistic datasets
  ☆48Updated 2 months ago
• tummfm / difftre
  Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting
  ☆36Updated last year
• nigalanakis / Crystal_Math
  Algorithms to analyze and predict molecular structures
  ☆24Updated 7 months ago
• mariogeiger / allegro-jax
  ☆22Updated 8 months ago
• grimme-lab / dxtb
  Efficient And Fully Differentiable Extended Tight-Binding
  ☆114Updated 2 weeks ago