Alternatives and similar repositories for AdsorbDiff

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

• ASK-Berkeley / EScAIP
  [NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential
  ☆52Updated 5 months ago
• OUnke / SpookyNet
  Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"
  ☆78Updated 3 years ago
• kyonofx / scdp
  [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"
  ☆35Updated 8 months ago
• ASK-Berkeley / MLFF-distill
  [ICLR 2025] Official Implementation of "Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy …
  ☆19Updated 4 months ago
• hspark1212 / chemeleon
  A text-guided diffusion model for crystal structure generation
  ☆62Updated 2 months ago
• AIforGreatGood / charge3net
  Higher-order equivariant neural networks for charge density prediction in materials
  ☆60Updated 6 months ago
• JoshRackers / equivariant_electron_density
  Generate and predict molecular electron densities with Euclidean Neural Networks
  ☆48Updated last year
• facebookresearch / JMP
  Code for “From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction”.
  ☆60Updated 10 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 2 years ago
• jla-gardner / graph-pes
  train and use graph-based ML models of potential energy surfaces
  ☆103Updated 3 weeks ago
• imagdau / aseMolec
  ☆29Updated last month
• sparks-baird / matbench-genmetrics
  Generative materials benchmarking metrics, inspired by guacamol and CDVAE.
  ☆40Updated last year
• MaxH1996 / PaiNN-in-PyG
  Implementing PaiNN in Pytorch Geometric
  ☆14Updated 3 years ago
• Arif-PhyChem / datasets_and_databases_4_MLPs
  ☆60Updated last week
• peterbjorgensen / DeepDFT
  Official implementation of DeepDFT model
  ☆82Updated 2 years ago
• ilyes319 / mace-tutorials
  Collection of tutorials to use the MACE machine learning force field.
  ☆48Updated 11 months ago
• ACEsuit / mace-off
  MACE-OFF23 models
  ☆42Updated 6 months ago
• gomes-lab / Mat2Spec
  ☆28Updated 3 years ago
• general-molecular-simulations / so3lr
  SO3krates and Universal Pairwise Force Field for Molecular Simulation
  ☆109Updated last month
• arthurkosmala / EwaldMP
  Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)
  ☆50Updated 2 years ago
• pfnet-research / charge_transfer_nnp
  Graph neural network potential with charge transfer
  ☆36Updated 3 years ago
• thomasple / FeNNol
  Force-field-enhanced Neural Networks optimized library
  ☆57Updated 3 weeks ago
• Shen-Group / E2GNN
  ☆18Updated 9 months ago
• TUM-DAML / gemnet_tf
  GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)
  ☆27Updated 2 years ago
• Fung-Lab / MatterTune
  A unified platform for fine-tuning atomistic foundation models in chemistry and materials science
  ☆57Updated last month
• PV-Lab / FTCP
  FTCP code
  ☆35Updated last year
• lanl / ALF
  A framework for performing active learning for training machine-learned interatomic potentials.
  ☆36Updated 4 months ago
• nityasagarjena / PaiNN-model
  This is a simple but efficient implementation of PaiNN-model for constructing machine learning interatomic potentials
  ☆21Updated 2 years ago
• matbench-submission-coGN / CrystalGNNs
  ☆10Updated last year
• nigalanakis / Crystal_Math
  Algorithms to analyze and predict molecular structures
  ☆21Updated last month