Alternatives and similar repositories for smooth-ot

Users that are interested in smooth-ot are comparing it to the libraries listed below

• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆29Updated 6 years ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆57Updated 6 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• icemiliang / pyvot
  A Python implementation of Monge optimal transportation
  ☆49Updated 2 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆69Updated 5 years ago
• agadetsky / pytorch-pl-variance-reduction
  [AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution
  ☆39Updated 4 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆53Updated 5 years ago
• hhcho / hyplinear
  MATLAB implementation of linear support vector classification in hyperbolic space
  ☆20Updated 7 years ago
• oskopek / mvae
  Mixed-curvature Variational Autoencoders (ICLR 2020)
  ☆65Updated 4 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆59Updated 4 years ago
• cunningham-lab / igr
  ☆30Updated 5 years ago
• AmirTag / OT-ICNN
  Learning the optimal transport map via input convex neural neworks
  ☆42Updated 5 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆51Updated 4 years ago
• GiulsLu / Sinkhorn-Barycenters
  Sinkhorn Barycenters via Frank-Wolfe algorithm
  ☆27Updated 5 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆37Updated 5 years ago
• izmailovpavel / flowgmm
  ☆149Updated 3 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆29Updated 6 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆85Updated 5 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated last year
• gpeyre / 2017-MCOM-unbalanced-ot
  L. Chizat, G. Peyré, B. Schmitzer, F-X. Vialard. Scaling Algorithms for Unbalanced Transport Problems. Preprint Arxiv:1607.05816, 2016.
  ☆43Updated 8 years ago
• mducoffe / Learning-Wasserstein-Embeddings
  Keras implementation of Deep Wasserstein Embeddings
  ☆48Updated 7 years ago
• hichamjanati / debiased-ot-barycenters
  ☆24Updated 4 years ago
• ermongroup / neuralsort
  Code for "Stochastic Optimization of Sorting Networks using Continuous Relaxations", ICLR 2019.
  ☆146Updated 2 years ago
• lezcano / expRNN
  Optimization with orthogonal constraints and on general manifolds
  ☆131Updated 5 years ago
• lchapel / partial-GW-for-PU
  Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs…
  ☆20Updated 5 years ago
• dimkal89 / rvae
  ☆37Updated 5 years ago