Alternatives and similar repositories for swgmm

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

• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆102Updated 7 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• icml-mcbn / mcbn
  ☆53Updated 7 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆90Updated 7 years ago
• fpcasale / GPPVAE
  Gaussian Process Prior Variational Autoencoder
  ☆86Updated 6 years ago
• cvlab-epfl / Power-Iteration-SVD
  Backpropagation-Friendly-Eigendecomposition
  ☆73Updated 5 years ago
• audeg / Sinkhorn-GAN
  Learning generative models with Sinkhorn Loss
  ☆30Updated 6 years ago
• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆29Updated 6 years ago
• SaynaEbrahimi / UCB
  Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020
  ☆76Updated 4 years ago
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆69Updated 5 years ago
• google / wasserstein-dist
  tensorflow implementation of the Wasserstein (aka optimal transport) distance
  ☆72Updated 4 years ago
• alexalemi / vib_demo
  ☆91Updated 3 years ago
• geniki / neural-processes
  PyTorch implementation of Neural Processes
  ☆88Updated 6 years ago
• maremun / swg
  Sliced Wasserstein Generator
  ☆23Updated 6 years ago
• 1Konny / WAE-pytorch
  ☆66Updated 6 years ago
• gpeyre / 2016-ICML-gromov-wasserstein
  Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.
  ☆74Updated 9 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• kimiandj / gsw
  ☆41Updated 5 years ago
• rythei / PyTorchOT
  implements optimal transport algorithms in pytorch
  ☆101Updated 3 years ago
• mingzhang-yin / ARM-gradient
  Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
  ☆27Updated 6 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆35Updated 5 years ago
• icemiliang / pyvot
  A Python implementation of Monge optimal transportation
  ☆49Updated 2 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆59Updated 4 years ago
• mducoffe / Learning-Wasserstein-Embeddings
  Keras implementation of Deep Wasserstein Embeddings
  ☆48Updated 7 years ago
• HeddaCohenIndelman / Learning-Gumbel-Sinkhorn-Permutations-w-Pytorch
  LEARNING LATENT PERMUTATIONS WITH GUMBEL-SINKHORN NETWORKS IMPLEMENTATION WITH PYTORCH
  ☆79Updated 2 years ago
• cunningham-lab / igr
  ☆30Updated 5 years ago
• yogeshbalaji / robustOT
  Robust Optimal Transport code
  ☆43Updated 3 years ago
• mikigom / large-scale-OT-mapping-TF
  Tensorflow Implementation of "Large-scale Optimal Transport and Mapping Estimation"(ICLR2018/NIPS 2017 OTML)
  ☆20Updated 7 years ago
• lin-shuyu / ladder-latent-data-distribution-modelling
  In this paper, we show that the performance of a learnt generative model is closely related to the model's ability to accurately represen…
  ☆41Updated 4 years ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆57Updated 6 years ago