Alternatives and similar repositories for Open-Catalyst-Dataset:

Users that are interested in Open-Catalyst-Dataset are comparing it to the libraries listed below

• OUnke / SpookyNet
  Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"
  ☆70Updated 2 years ago
• janosh / matbench-discovery
  An evaluation framework for machine learning models simulating high-throughput materials discovery.
  ☆136Updated this week
• learningmatter-mit / NeuralForceField
  Neural Network Force Field based on PyTorch
  ☆267Updated last month
• materialsproject / matbench
  Matbench: Benchmarks for materials science property prediction
  ☆147Updated 7 months ago
• txie-93 / gdynet
  Unsupervised learning of atomic scale dynamics from molecular dynamics.
  ☆81Updated 3 years ago
• BingqingCheng / ASAP
  ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.
  ☆144Updated 8 months ago
• chenruduan / OAReactDiff
  An object-aware diffusion model for generating chemical reactions
  ☆121Updated 9 months ago
• luigibonati / mlcolvar
  A unified framework for machine learning collective variables for enhanced sampling simulations
  ☆99Updated last month
• stefanch / sGDML
  sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model
  ☆147Updated last year
• TUM-DAML / gemnet_pytorch
  GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)
  ☆194Updated last year
• ulissigroup / amptorch
  AMPtorch: Atomistic Machine Learning Package (AMP) - PyTorch
  ☆60Updated last year
• MDIL-SNU / SevenNet
  SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.
  ☆156Updated this week
• PV-Lab / FTCP
  FTCP code
  ☆33Updated last year
• mir-group / pair_allegro
  LAMMPS pair style for Allegro deep learning interatomic potentials with parallelization support
  ☆41Updated 5 months ago
• Andrew-S-Rosen / QMOF
  The QMOF Database: A database of quantum-mechanical properties for metal-organic frameworks.
  ☆138Updated last month
• thorben-frank / mlff
  Build neural networks for machine learning force fields with JAX
  ☆110Updated last month
• Open-Catalyst-Project / AdsorbML
  Corresponding dataset and tools for the AdsorbML manuscript.
  ☆40Updated last month
• deepmodeling / DMFF
  DMFF (Differentiable Molecular Force Field) is a Jax-based python package that provides a full differentiable implementation of molecular…
  ☆171Updated 5 months ago
• kyonofx / MDsim
  [TMLR 2023] Training and simulating MD with ML force fields
  ☆111Updated 4 months ago
• ACEsuit / mace-mp
  MACE-MP models
  ☆81Updated this week
• usnistgov / jarvis_leaderboard
  A large scale benchmark of materials design methods: https://www.nature.com/articles/s41524-024-01259-w
  ☆65Updated last week
• deepmodeling / deepks-kit
  a package for developing machine learning-based chemically accurate energy and density functional models
  ☆105Updated 5 months ago
• aiqm / ANI1x_datasets
  The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for organic molecules.
  ☆63Updated 2 years ago
• IntelLabs / matsciml
  Open MatSci ML Toolkit is a framework for prototyping and scaling out deep learning models for materials discovery supporting widely used…
  ☆170Updated this week
• materialsvirtuallab / matgl
  Graph deep learning library for materials
  ☆320Updated this week
• hjkgrp / molSimplify
  molSimplify code
  ☆183Updated this week
• Tinystormjojo / geo-CGNN
  ☆33Updated 8 months ago
• facebookresearch / JMP
  Code for “From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction”.
  ☆49Updated 5 months ago
• atomistic-machine-learning / G-SchNet
  G-SchNet - a generative model for 3d molecular structures
  ☆135Updated last year
• hsulab / GDPy
  Generating Deep Potential with Python
  ☆65Updated this week