Alternatives and similar repositories for DADApy

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

• noegroup / bgflow
  Boltzmann Generators and Normalizing Flows in PyTorch
  ☆175Updated last year
• senya-ashukha / simple-equivariant-gnn
  A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks
  ☆139Updated 3 years ago
• google-research / e3x
  E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.
  ☆108Updated 6 months ago
• wwang2 / Coarse-Graining-Auto-encoders
  ☆40Updated 3 years ago
• ma921 / BASQ
  (NeurIPS 2022) Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination
  ☆19Updated last year
• aspuru-guzik-group / phoenics
  Phoenics: Bayesian optimization for efficient experiment planning
  ☆93Updated 6 years ago
• leojklarner / gauche
  A Library for Gaussian Processes in Chemistry
  ☆240Updated 11 months ago
• smsharma / eqnn-jax
  Annotated implementations of equivariant (graph) neural networks in Jax: EGNN, SEGNN, NequIP.
  ☆39Updated 7 months ago
• proteneer / timemachine
  Differentiate all the things!
  ☆157Updated last week
• plainerman / Variational-Doob
  Lagrangian formulation of Doob's h-transform allowing for efficient rare event sampling
  ☆52Updated 6 months ago
• materials-data-facility / awesome-bayesian-optimization
  ☆42Updated last year
• blondegeek / e3nn_tutorial
  repository and website for tutorials on 3d Euclidean equivariant neural networks
  ☆75Updated 4 years ago
• lollcat / se3-augmented-coupling-flows
  SE(3) Equivariant Augmented Coupling Flows. NeurIPS 2023.
  ☆24Updated last year
• ur-whitelab / maxent
  MaxEnt code for fitting simulation outcomes/statistical models to observations
  ☆16Updated 3 years ago
• ACEsuit / mace-layer
  Higher order equivariant graph neural networks for 3D point clouds
  ☆44Updated 2 years ago
• lie-nn / lie-nn
  Tools for building equivariant polynomials on reductive Lie groups.
  ☆35Updated 2 years ago
• noegroup / paper_boltzmann_generators
  ☆89Updated 3 years 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…
  ☆59Updated 5 months ago
• google-deepmind / flows_for_atomic_solids
  ☆53Updated 2 years ago
• aspuru-guzik-group / olympus
  Olympus: a benchmarking framework for noisy optimization and experiment planning
  ☆87Updated 10 months ago
• e3nn / e3nn-jax
  jax library for E3 Equivariant Neural Networks
  ☆216Updated last month
• psipred / cgdms
  Differentiable molecular simulation of proteins with a coarse-grained potential
  ☆56Updated 6 months ago
• LarsHoldijk / SOCTransitionPaths
  ☆32Updated 3 years ago
• sparks-baird / dist-matrix
  Fast Numba-enabled CPU and GPU computations of Earth Mover's (scipy.stats.wasserstein_distance) and Euclidean distances.
  ☆18Updated 9 months ago
• learningmatter-mit / Atomistic-Adversarial-Attacks
  Code for performing adversarial attacks on atomistic systems using NN potentials
  ☆40Updated 3 years ago
• tiwarylab / DynamicsAE
  A deep learning-based framework to uniquely identify an uncorrelated, isometric and meaningful latent representation.
  ☆17Updated 2 years ago
• vgsatorras / en_flows
  ☆59Updated 3 years ago
• JacksonBurns / astartes
  Better Data Splits for Machine Learning
  ☆88Updated last week
• ACEsuit / mace-jax
  Equivariant machine learning interatomic potentials in JAX.
  ☆75Updated this week
• risilab / cormorant
  Codebase for Cormorant Neural Networks
  ☆60Updated 3 years ago