Alternatives and similar repositories for EScAIP

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

• AIforGreatGood / charge3net
  [npj Comp. Mat.] Higher-order equivariant neural networks for charge density prediction in materials
  ☆71Updated 11 months ago
• JoshRackers / equivariant_electron_density
  Generate and predict molecular electron densities with Euclidean Neural Networks
  ☆49Updated 2 years ago
• vldgroup / graph-pes
  train and use graph-based ML models of potential energy surfaces
  ☆119Updated last month
• kyonofx / scdp
  [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"
  ☆39Updated last year
• learningmatter-mit / liflow
  Flow matching for accelerated simulation of atomic transport
  ☆56Updated 3 months ago
• OUnke / SpookyNet
  Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"
  ☆85Updated 3 years ago
• peterbjorgensen / DeepDFT
  Official implementation of DeepDFT model
  ☆87Updated 2 years ago
• AdeeshKolluru / AdsorbDiff
  [ICML'24] Adsorbate Placement via Conditional Denoising Diffusion
  ☆23Updated last year
• facebookresearch / JMP
  Code for “From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction”.
  ☆62Updated last year
• 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
• atomicarchitects / DeNS
  [TMLR 2024 J2C Certification] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields
  ☆40Updated 11 months ago
• hspark1212 / chemeleon
  A text-guided diffusion model for crystal structure generation
  ☆74Updated 8 months ago
• arthurkosmala / EwaldMP
  Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)
  ☆51Updated 2 years ago
• sparks-baird / matbench-genmetrics
  Generative materials benchmarking metrics, inspired by guacamol and CDVAE.
  ☆40Updated last year
• ACEsuit / mace-off
  MACE-OFF23 models
  ☆59Updated last year
• imagdau / aseMolec
  ☆32Updated this week
• nigalanakis / Crystal_Math
  Algorithms to analyze and predict molecular structures
  ☆24Updated 7 months ago
• lab-cosmo / torch-pme
  Particle-mesh based calculations of long-range interactions in PyTorch
  ☆70Updated last week
• ACEsuit / mace-jax
  Equivariant machine learning interatomic potentials in JAX.
  ☆83Updated last week
• thorben-frank / mlff
  Build neural networks for machine learning force fields with JAX
  ☆132Updated 8 months ago
• ASK-Berkeley / StABlE-Training
  [TMLR 2025] Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators
  ☆15Updated 2 months ago
• davkovacs / BOTNet-datasets
  This repo contains the datasets used for the paper The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.
  ☆19Updated 3 years ago
• Fung-Lab / MatterTune
  A unified platform for fine-tuning atomistic foundation models in chemistry and materials science
  ☆71Updated this week
• kyonofx / MDsim
  [TMLR 2023] Training and simulating MD with ML force fields
  ☆115Updated 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
• FeNNol-tools / FeNNol
  Force-field-enhanced Neural Networks optimized library
  ☆81Updated last month
• mariogeiger / nequip-jax
  ☆23Updated 2 years ago
• eltonpan / zeosyn_gen
  DiffSyn: A Generative Diffusion Approach to Materials Synthesis Planning (Nature Computational Science, under proof)
  ☆25Updated last month
• mir-group / pair_nequip_allegro
  LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials
  ☆59Updated 4 months ago
• schwallergroup / AdsMT
  Multimodal Transformer for Predicting Global Minimum Adsorption Energy
  ☆27Updated 10 months ago