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
  ☆58Updated 4 months ago
• learningmatter-mit / liflow
  Flow matching for accelerated simulation of atomic transport
  ☆56Updated 3 months ago
• 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
• OUnke / SpookyNet
  Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"
  ☆85Updated 3 years ago
• facebookresearch / JMP
  Code for “From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction”.
  ☆62Updated last year
• hspark1212 / chemeleon
  A text-guided diffusion model for crystal structure generation
  ☆74Updated 8 months ago
• 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
• arthurkosmala / EwaldMP
  Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)
  ☆51Updated 2 years ago
• imagdau / aseMolec
  ☆32Updated last week
• kyonofx / scdp
  [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"
  ☆39Updated last year
• sparks-baird / matbench-genmetrics
  Generative materials benchmarking metrics, inspired by guacamol and CDVAE.
  ☆40Updated last year
• Fung-Lab / MatterTune
  A unified platform for fine-tuning atomistic foundation models in chemistry and materials science
  ☆71Updated this week
• matbench-submission-coGN / CrystalGNNs
  ☆11Updated 2 years ago
• ACEsuit / mace-off
  MACE-OFF23 models
  ☆59Updated last year
• 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
• vldgroup / graph-pes
  train and use graph-based ML models of potential energy surfaces
  ☆119Updated last month
• peterbjorgensen / DeepDFT
  Official implementation of DeepDFT model
  ☆87Updated 2 years ago
• schwallergroup / AdsMT
  Multimodal Transformer for Predicting Global Minimum Adsorption Energy
  ☆27Updated 10 months ago
• ACEsuit / mace-tutorials
  Collection of tutorials to use the MACE machine learning force field.
  ☆52Updated 2 weeks ago
• atomistic-machine-learning / schnetpack-gschnet
  G-SchNet extension for SchNetPack
  ☆64Updated 2 months ago
• llnl / graphite
  A repository for implementing graph network models based on atomic structures.
  ☆104Updated last year
• nityasagarjena / PaiNN-model
  This is a simple but efficient implementation of PaiNN-model for constructing machine learning interatomic potentials
  ☆25Updated 3 years ago
• Shen-Group / E2GNN
  ☆24Updated last year
• gomes-lab / Mat2Spec
  ☆29Updated 3 years 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
• nigalanakis / Crystal_Math
  Algorithms to analyze and predict molecular structures
  ☆24Updated 7 months ago
• seonghann / tsdiff
  Diffusion model for transition state prediction
  ☆46Updated 2 years ago
• hspark1212 / DAC-SIM
  A molecular simulation package integrating MLFFs in MOFs for DAC
  ☆41Updated 3 months ago
• pfnet-research / charge_transfer_nnp
  Graph neural network potential with charge transfer
  ☆37Updated 3 years ago