Alternatives and similar repositories for MMD-gradient-flow:

Users that are interested in MMD-gradient-flow are comparing it to the libraries listed below

• AmirTag / OT-ICNN
  Learning the optimal transport map via input convex neural neworks
  ☆41Updated 4 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆51Updated 6 months ago
• ermongroup / f-dre
  Featurized Density Ratio Estimation
  ☆20Updated 3 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆44Updated last year
• franciscovargas / GP_Sinkhorn
  GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134
  ☆22Updated 2 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆44Updated last year
• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆28Updated 5 years ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆31Updated 2 years ago
• dimkal89 / rvae
  ☆38Updated 4 years ago
• cscarv / riemannian-metric-learning-ot
  ☆17Updated last year
• audeg / Sinkhorn-GAN
  Learning generative models with Sinkhorn Loss
  ☆28Updated 6 years ago
• iamalexkorotin / Wasserstein2Benchmark
  A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)
  ☆38Updated 2 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 4 years ago
• noamroze / moser_flow
  ☆16Updated 2 years ago
• lgresele / independent-mechanism-analysis
  Code for the paper: "Independent mechanism analysis, a new concept?"
  ☆24Updated last year
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 5 years ago
• ratschlab / SVGP-VAE
  Tensorflow implementation for the SVGP-VAE model.
  ☆21Updated 3 years ago
• siplab-gt / VAELLS
  Code for "Variational Autoencoder with Learned Latent Structure"
  ☆33Updated 3 years ago
• cunningham-lab / igr
  ☆31Updated 4 years ago
• changliu00 / AWGF
  Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)
  ☆22Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• justkolesov / Wasserstein1Benchmark
  A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).
  ☆20Updated 5 months ago
• iamalexkorotin / Wasserstein2GenerativeNetworks
  PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)
  ☆52Updated 2 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆30Updated 3 years ago
• J-zin / energy-discrepancy
  NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
  ☆14Updated 3 months ago
• AkinoriTanaka-phys / DOT
  code submission to NeurIPS2019
  ☆13Updated last year
• hichamjanati / debiased-ot-barycenters
  ☆24Updated 3 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆57Updated 6 years ago
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆53Updated 2 years ago
• iffsid / DReG-PyTorch
  A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"
  ☆18Updated 5 years ago