Alternatives and similar repositories for large-scale-OT-mapping-TF

Users that are interested in large-scale-OT-mapping-TF are comparing it to the libraries listed below

• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆91Updated 7 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.
  ☆75Updated 9 years ago
• skolouri / swgmm
  Sliced Wasserstein Distance for Learning Gaussian Mixture Models
  ☆66Updated 2 years ago
• 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
• bruno-31 / GAN-manifold-regularization
  This is the code for our paper: Semi-Supervised Learning With GANs: Revisiting Manifold Regularization (ICLR 2018)
  ☆44Updated 6 years ago
• 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
• MichaelArbel / Scaled-MMD-GAN
  Scaled MMD GAN
  ☆36Updated 6 years ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆57Updated 6 years ago
• audeg / StochasticOT
  Stochastic Optimization for Optimal Transport
  ☆22Updated 9 years ago
• fpcasale / GPPVAE
  Gaussian Process Prior Variational Autoencoder
  ☆86Updated 6 years ago
• LiamCattell / optimaltransport
  Optimal transport transforms
  ☆23Updated 7 years ago
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆69Updated 5 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆81Updated 6 years ago
• arolet / wasserstein-dictionary-learning
  A matlab toolbox to perform Wasserstein Dictionary Learning or NMF
  ☆32Updated 9 years ago
• google / wasserstein-dist
  tensorflow implementation of the Wasserstein (aka optimal transport) distance
  ☆72Updated 4 years ago
• ermongroup / a-nice-mc
  Code for "A-NICE-MC: Adversarial Training for MCMC"
  ☆125Updated 7 years ago
• bfarzin / pytorch_aae
  Pytorch Adversarial Auto Encoder (AAE)
  ☆87Updated 6 years ago
• adler-j / wasserstein_inverse_problems
  Code for the article "Learning to solve inverse problems using Wasserstein loss"
  ☆28Updated 8 years ago
• rflamary / JDOT
  Joint distribution optimal transportation for domain adaptation
  ☆102Updated 7 years ago
• YingzhenLi / Dropout_BBalpha
  Implementations of the ICML 2017 paper (with Yarin Gal)
  ☆38Updated 7 years ago
• tkkiran / Robust-Conditional-GAN
  Code for reproducing results from our paper, Robustness of conditional GANs to noisy labels, NIPS 2018
  ☆40Updated 6 years ago
• casperkaae / LVAE
  Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"
  ☆103Updated 9 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 5 years ago
• dimkastan / PyTorch-Spectral-clustering
  [Under development]- Implementation of various methods for dimensionality reduction and spectral clustering implemented with Pytorch
  ☆163Updated 8 years ago
• chervud / AGD-vs-Sinkhorn
  Code for http://proceedings.mlr.press/v80/dvurechensky18a.html
  ☆17Updated 7 years ago
• rflamary / OTML_DS3_2018
  Practical sessions for the Optimal Transport and Machine learning course at DS3 2018
  ☆92Updated 7 years ago
• RobRomijnders / bayes_nn
  Uncertainty interpretations of the neural network
  ☆32Updated 7 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago