Alternatives and similar repositories for equivariant_electron_density

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

• peterbjorgensen / DeepDFT
  Official implementation of DeepDFT model
  ☆79Updated 2 years ago
• ACEsuit / mace-off
  MACE-OFF23 models
  ☆37Updated 4 months ago
• OUnke / SpookyNet
  Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"
  ☆76Updated 3 years ago
• mir-group / pair_nequip_allegro
  LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials
  ☆45Updated 3 weeks ago
• lab-cosmo / torch-pme
  Particle-mesh based calculations of long-range interactions in PyTorch
  ☆51Updated 2 weeks ago
• general-molecular-simulations / so3lr
  SO3krates and Universal Pairwise Force Field for Molecular Simulation
  ☆104Updated last week
• jla-gardner / graph-pes
  train and use graph-based ML models of potential energy surfaces
  ☆97Updated last week
• imagdau / aseMolec
  ☆26Updated last week
• davkovacs / BOTNet-datasets
  This repo contains the datasets used for the paper The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.
  ☆18Updated 2 years ago
• grimme-lab / dxtb
  Efficient And Fully Differentiable Extended Tight-Binding
  ☆94Updated 2 weeks ago
• Arif-PhyChem / datasets_and_databases_4_MLPs
  ☆58Updated last month
• ASK-Berkeley / EScAIP
  [NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential
  ☆51Updated 3 months ago
• nigalanakis / Crystal_Math
  Algorithms to analyze and predict molecular structures
  ☆19Updated 9 months ago
• uiocompcat / tmQM
  tmQM dataset files
  ☆53Updated 3 months ago
• nityasagarjena / PaiNN-model
  This is a simple but efficient implementation of PaiNN-model for constructing machine learning interatomic potentials
  ☆20Updated 2 years ago
• BingqingCheng / ab-initio-thermodynamics-of-water
  “Ab initio thermodynamics of liquid and solid water” Bingqing Cheng, Edgar A. Engel, JÖrg Behler, Christoph Dellago and Michele Ceriotti…
  ☆27Updated 5 years ago
• duartegroup / mlp-train
  MLP training for molecular systems
  ☆49Updated this week
• ulissigroup / finetuna
  Active Learning for Machine Learning Potentials
  ☆55Updated last year
• BingqingCheng / cace
  ☆77Updated this week
• tummfm / difftre
  Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting
  ☆31Updated last year
• luigibonati / data-driven-CVs
  Supporting material for the paper "Data driven collective variables for enhanced sampling"
  ☆18Updated last year
• ilyes319 / mace-tutorials
  Collection of tutorials to use the MACE machine learning force field.
  ☆47Updated 9 months ago
• sparks-baird / matbench-genmetrics
  Generative materials benchmarking metrics, inspired by guacamol and CDVAE.
  ☆40Updated last year
• hspark1212 / chemeleon
  A text-guided diffusion model for crystal structure generation
  ☆60Updated 3 weeks ago
• zhaoqy1996 / YARP
  ☆46Updated 2 years ago
• zadorlab / sella
  A Python software package for saddle point optimization and minimization of atomic systems.
  ☆105Updated 8 months ago
• zachglick / AP-Net
  AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials
  ☆15Updated 4 years ago
• aiqm / ANI1x_datasets
  The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for organic molecules.
  ☆64Updated 3 years ago
• THGLab / NewtonNet
  A Newtonian message passing network for deep learning of interatomic potentials and forces
  ☆43Updated last week
• Exscientia / physicsml
  A package for all physics based/related models
  ☆52Updated 9 months ago