Alternatives and similar repositories for paper_boltzmann_generators

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

• risilab / cormorant
  Codebase for Cormorant Neural Networks
  ☆60Updated 3 years ago
• blondegeek / e3nn_tutorial
  repository and website for tutorials on 3d Euclidean equivariant neural networks
  ☆73Updated 4 years ago
• wwang2 / Coarse-Graining-Auto-encoders
  ☆40Updated 3 years ago
• atomistic-machine-learning / G-SchNet
  G-SchNet - a generative model for 3d molecular structures
  ☆142Updated 2 years ago
• markovmodel / deeptime
  Deep learning meets molecular dynamics.
  ☆182Updated 6 years ago
• noegroup / bgflow
  Boltzmann Generators and Normalizing Flows in PyTorch
  ☆172Updated last year
• stefanch / sGDML
  sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model
  ☆155Updated 2 months ago
• noegroup / EDMnets
  parameterizing valid Euclidean distance matrices (EDMs) via neural networks
  ☆20Updated 5 years ago
• kyonofx / MDsim
  [TMLR 2023] Training and simulating MD with ML force fields
  ☆112Updated 9 months ago
• markovmodel / mdshare
  Get access to our MD data files.
  ☆29Updated last year
• coarse-graining / cgnet
  learning coarse-grained force fields
  ☆63Updated 3 years ago
• torchmd / torchmd-cg
  Example to fit parameters and run CG simulations using TorchMD and Schnet
  ☆47Updated 3 years ago
• psipred / cgdms
  Differentiable molecular simulation of proteins with a coarse-grained potential
  ☆55Updated 4 months ago
• torchmd / torchmd-protein-thermodynamics
  Tutorials and data necessary to reproduce the results of publication Machine Learning Coarse-Grained Potentials of Protein Thermodynamics
  ☆89Updated 7 months ago
• openmm / spice-dataset
  A collection of QM data for training potential functions
  ☆180Updated 6 months ago
• kyonofx / mlcgmd
  [TMLR 2023] Simulate time-integrated coarse-grained MD with multi-scale graph neural networks
  ☆73Updated 2 years ago
• NREL / nfp
  Keras layers for end-to-end learning with rdkit and pymatgen
  ☆60Updated last year
• luigibonati / deep-learning-slow-modes
  Supporting data for the manuscript "Deep learning the slow modes for rare events sampling"
  ☆20Updated last year
• torchmd / mdgrad
  Pytorch differentiable molecular dynamics
  ☆180Updated 2 years ago
• microsoft / timewarp
  Timewarp is a research project using deep learning to accelerate molecular dynamics simulation.
  ☆56Updated last year
• hsidky / srv
  ☆14Updated 5 years ago
• openmm / NNPOps
  High-performance operations for neural network potentials
  ☆93Updated 6 months ago
• proteneer / timemachine
  Differentiate all the things!
  ☆157Updated last month
• john-bradshaw / synthesis-dags
  Code for our paper "Barking up the right tree: an approach to search over molecule synthesis DAGs"
  ☆47Updated last year
• gncs / molgym
  Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
  ☆127Updated 2 years ago
• hoffmannjordan / Encoding-Decoding-3D-Crystals
  "Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures", Jordan Hoffmann, Louis Maestrati, Yoshihide Sawada, Jian Tang, Je…
  ☆34Updated 5 years ago
• atomistic-machine-learning / SchNOrb
  Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions
  ☆69Updated 5 years ago
• wwang2 / CoarseGrainingVAE
  Geometric super-resolution for molecular geometries
  ☆41Updated 3 years ago
• ASK-Berkeley / OM-TPS
  [ICML 2025] Repurposing pre-trained score-based generative models for transition path sampling by minimizing the Onsager-Machlup (OM) act…
  ☆18Updated last month
• thorben-frank / mlff
  Build neural networks for machine learning force fields with JAX
  ☆124Updated 2 months ago