Alternatives and similar repositories for flows_for_atomic_solids

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

• gerkone / segnn-jax
  Steerable E(3) GNN in jax
  ☆24Updated 2 years ago
• google-research / e3x
  E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.
  ☆109Updated 6 months ago
• mdsunivie / deeperwin
  DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electr…
  ☆62Updated 6 months ago
• smsharma / eqnn-jax
  Annotated implementations of equivariant (graph) neural networks in Jax: EGNN, SEGNN, NequIP.
  ☆39Updated 7 months ago
• n-gao / pesnet
  Reference implementation of "Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions" (ICLR, 2022) and "Sampling-f…
  ☆31Updated last year
• deepchem / jaxchem
  JAXChem is a JAX-based deep learning library for complex and versatile chemical modeling
  ☆80Updated 5 years ago
• lie-nn / lie-nn
  Tools for building equivariant polynomials on reductive Lie groups.
  ☆35Updated 2 years ago
• e3nn / e3nn-jax
  jax library for E3 Equivariant Neural Networks
  ☆216Updated 2 months ago
• lollcat / se3-augmented-coupling-flows
  SE(3) Equivariant Augmented Coupling Flows. NeurIPS 2023.
  ☆24Updated last year
• blondegeek / e3nn_symm_breaking
  Code repository for "Finding symmetry breaking order parameters with Euclidean Neural Networks"
  ☆16Updated 4 years ago
• maxxxzdn / jax-geometric
  Implementation of various equivariant models in JAX
  ☆12Updated last year
• ACEsuit / mace-layer
  Higher order equivariant graph neural networks for 3D point clouds
  ☆45Updated 2 years ago
• CCQC / Quax
  Arbitrary-order derivatives of popular electronic structure methods, such as Hartree-Fock and coupled cluster theory.
  ☆69Updated last year
• proteneer / timemachine
  Differentiate all the things!
  ☆158Updated last month
• ACEsuit / mace-jax
  Equivariant machine learning interatomic potentials in JAX.
  ☆78Updated this week
• torchmd / mdgrad
  Pytorch differentiable molecular dynamics
  ☆179Updated 3 years ago
• DavidRuhe / clifford-group-equivariant-neural-networks
  Code used by the "Clifford Group Equivariant Neural Networks" paper.
  ☆84Updated last year
• mala-project / mala
  Materials Learning Algorithms. A framework for machine learning materials properties from first-principles data.
  ☆97Updated last month
• fabiannagel / schnax
  An implementation of SchNet in JAX and JAX-MD.
  ☆17Updated 3 years ago
• diffqc / dqc
  Differentiable Quantum Chemistry (only Differentiable Density Functional Theory and Hartree Fock at the moment)
  ☆118Updated 3 years ago
• XanaduAI / GradDFT
  GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine l…
  ☆107Updated last year
• wwang2 / Coarse-Graining-Auto-encoders
  ☆40Updated 3 years ago
• ChemAI-Lab / ofdft_nflows
  Nomalizing flows for orbita-free DFT
  ☆11Updated last year
• metatensor / metatensor
  Self-describing sparse tensor data format for atomistic machine learning and beyond
  ☆87Updated 2 weeks ago
• tomdbar / naqs-for-quantum-chemistry
  Supporting code for "Autoregressive neural-network wavefunctions for ab initio quantum chemistry".
  ☆41Updated 3 years ago
• psipred / cgdms
  Differentiable molecular simulation of proteins with a coarse-grained potential
  ☆56Updated 6 months ago
• mariogeiger / allegro-jax
  ☆22Updated 5 months ago
• li012589 / neuralCT
  Pytorch implement of the paper Neural Canonical Transformation with Symplectic Flows
  ☆30Updated 5 years ago
• learningmatter-mit / Atomistic-Adversarial-Attacks
  Code for performing adversarial attacks on atomistic systems using NN potentials
  ☆40Updated 3 years ago
• sail-sg / jax_xc
  Exchange correlation functionals translated from libxc to jax
  ☆46Updated 7 months ago