Alternatives and similar repositories for Large-Scale-Wasserstein-Gradient-Flows

Users that are interested in Large-Scale-Wasserstein-Gradient-Flows are comparing it to the libraries listed below

• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆53Updated 11 months ago
• necludov / jam
  Implementation of Action Matching
  ☆44Updated 2 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 2 years ago
• justkolesov / Wasserstein1Benchmark
  A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).
  ☆21Updated 9 months ago
• franciscovargas / GP_Sinkhorn
  GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134
  ☆23Updated 3 years ago
• noamroze / moser_flow
  ☆17Updated 3 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆103Updated last year
• noegroup / stochastic_normalizing_flows
  Stochastic Normalizing Flows
  ☆76Updated 3 years ago
• sbyebss / variational_wgf
  [ICML2022] Variational Wasserstein gradient flow
  ☆22Updated 2 years ago
• iamalexkorotin / Wasserstein2Benchmark
  A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)
  ☆41Updated 3 years ago
• J-zin / energy-discrepancy
  NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
  ☆16Updated 8 months ago
• facebookresearch / SOC-matching
  Code release for "Stochastic Optimal Control Matching"
  ☆35Updated 10 months ago
• necludov / action-matching
  Implementation of Action Matching for the Schrödinger equation
  ☆24Updated 2 years ago
• necludov / wl-mechanics
  ☆32Updated last year
• AmirTag / OT-ICNN
  Learning the optimal transport map via input convex neural neworks
  ☆41Updated 5 years ago
• DenisBless / variational_sampling_methods
  [ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".
  ☆35Updated 6 months ago
• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆38Updated 2 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• ngushchin / EntropicNeuralOptimalTransport
  Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).
  ☆37Updated last year
• vdutor / neural-diffusion-processes
  Neural Diffusion Processes
  ☆81Updated 10 months ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 3 years ago
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆10Updated 2 years ago
• Daulbaev / IRDM
  ☆11Updated 4 years ago
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆48Updated last week
• hmdolatabadi / LRS_NF
  [AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".
  ☆20Updated 2 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated 11 months ago
• CW-Huang / CP-Flow
  Convex potential flows
  ☆83Updated 3 years ago
• DanieleGammelli / pyro-torch-normalizing-flows
  Implementations of Normalizing Flows in Pytorch/Pyro
  ☆19Updated 5 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• ngushchin / EntropicOTBenchmark
  Entropic Optimal Transport Benchmark (NeurIPS 2023).
  ☆24Updated last year