Alternatives and similar repositories for self-refining-dft

Users that are interested in self-refining-dft are comparing it to the libraries listed below

• grimme-lab / MindlessGen
  Mindless molecule generator in a Python package.
  ☆27Updated 2 months ago
• tummfm / chemtrain
  Training Neural Network potentials through customizable routines in JAX.
  ☆34Updated last week
• digital-chemistry-laboratory / coulson
  Python code for Hückel and Pariser-Parr-Pople molecular orbital theory
  ☆15Updated last year
• dftd4 / tad-dftd4
  PyTorch Autodiff DFT-D4 Implementation.
  ☆20Updated 2 weeks ago
• RodrigoAVargasHdz / huxel
  Huxel: Huckel model + JAX (parameter optimization)
  ☆10Updated 2 years ago
• THGLab / MLHessian-TSopt
  ☆17Updated 10 months ago
• learningmatter-mit / Atomistic-Adversarial-Attacks
  Code for performing adversarial attacks on atomistic systems using NN potentials
  ☆38Updated 2 years ago
• lab-cosmo / atomistic-cookbook
  A collection of simulation recipes for the atomic-scale modeling of materials and molecules
  ☆23Updated this week
• Fung-Lab / StructRepGen
  Atomic Structure Generation from Reconstructing Structural Fingerprints
  ☆15Updated 2 years ago
• corinwagen / pymsym
  molecular point group symmetry lib
  ☆11Updated 6 months ago
• metatensor / metatrain
  Training and evaluating machine learning models for atomistic systems.
  ☆33Updated this week
• atomicarchitects / symphony
  [ICLR'24] Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for Molecule Generation
  ☆23Updated 4 months ago
• zubatyuk / aimnet2
  AIMNet2: Fast, accurate and transferable neural network interatomic potential
  ☆18Updated 8 months ago
• lanl / PYSEQM
  an interface to semi-empirical quantum chemistry methods implemented with pytorch
  ☆52Updated this week
• abhijeetgangan / a2c_ase
  An ASE-friendly implementation of the amorphous-to-crystalline (a2c) workflow.
  ☆11Updated 3 months ago
• ASK-Berkeley / StABlE-Training
  [TMLR 2025] Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators
  ☆14Updated 3 months ago
• Abdelazim-Abdelgawwad / easyPARM
  easyPARM is a computational tool developed to simplify the derivation of force field parameters for metal-containing molecular systems an…
  ☆18Updated this week
• RokasEl / simgen
  Zero Shot Molecular Generation via Similarity Kernels
  ☆20Updated 3 weeks ago
• THGLab / NewtonNet
  A Newtonian message passing network for deep learning of interatomic potentials and forces
  ☆43Updated last week
• theochem / denspart
  Atoms-in-molecules density partitioning schemes based on stockholder recipe
  ☆22Updated 2 weeks ago
• atomistic-machine-learning / field_schnet
  ☆19Updated 3 years ago
• raghurama123 / qm9pack
  A Python package for data-mining the QM9 dataset
  ☆17Updated 3 months ago
• ASK-Berkeley / MLFF-distill
  [ICLR 2025] Official Implementation of "Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy …
  ☆15Updated 2 months ago
• graphcore-research / mess
  MESS: Modern Electronic Structure Simulations
  ☆20Updated 9 months ago
• learningmatter-mit / alchemical-mlip
  Alchemical machine learning interatomic potentials
  ☆29Updated 7 months ago
• kyonofx / scdp
  [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"
  ☆35Updated 6 months ago
• bkoz37 / labutil
  Lab materials for MIT 3.320 and Harvard AP 275 courses on atomistic modeling
  ☆16Updated 4 years ago
• hatemhelal / mess
  MESS: Modern Electronic Structure Simulations
  ☆31Updated 2 months ago
• cgrambow / ard_gsm
  Automated reaction discovery and dataset generation with the growing string method
  ☆20Updated 5 years ago
• rinikerlab / EquivariantMultipoleGNN
  Equivariant GNN for the prediction of atomic multipoles up to quadrupoles.
  ☆30Updated 3 years ago