Alternatives and similar repositories for Learning-Wasserstein-Embeddings

Users that are interested in Learning-Wasserstein-Embeddings are comparing it to the libraries listed below

• kingofspace0wzz / wae-rnf-lm
  Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…
  ☆63Updated 5 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆90Updated 7 years ago
• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆102Updated 6 years ago
• google / gumbel_sinkhorn
  ☆76Updated 7 years ago
• msobroza / SparsemaxPytorch
  SparseMax activation function implementation (ICML 2016) (PyTorch)
  ☆28Updated 7 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• rythei / PyTorchOT
  implements optimal transport algorithms in pytorch
  ☆100Updated 3 years ago
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆69Updated 5 years ago
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 8 years ago
• yaohungt / Adaptive-Regularization-Neural-Network
  [NeurIPS'19] [PyTorch] Adaptive Regularization in NN
  ☆68Updated 5 years ago
• claying / OTK
  A Pytorch implementation of the optimal transport kernel embedding
  ☆118Updated 4 years ago
• paruby / Wasserstein-Auto-Encoders
  Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761
  ☆37Updated 7 years ago
• sajadn / Exemplar-VAE
  Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation
  ☆68Updated 4 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆35Updated 5 years ago
• LuisArmandoPerez / DiffusionVAE
  ☆29Updated 3 years ago
• maremun / swg
  Sliced Wasserstein Generator
  ☆23Updated 6 years ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆56Updated 6 years ago
• agadetsky / pytorch-pl-variance-reduction
  [AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution
  ☆38Updated 4 years ago
• kefirski / variational_dropout
  Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
  ☆49Updated 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.
  ☆74Updated 9 years ago
• vithursant / VAE-Gumbel-Softmax
  An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU…
  ☆72Updated 7 years ago
• Cyanogenoid / fspool
  [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling
  ☆42Updated last year
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 5 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• KyleGoyette / nnRNN
  ☆24Updated 5 years ago
• wouterkool / estimating-gradients-without-replacement
  Estimating Gradients for Discrete Random Variables by Sampling without Replacement
  ☆40Updated 5 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• mblondel / smooth-ot
  Python implementation of smooth optimal transport.
  ☆60Updated 4 years ago
• hichamjanati / debiased-ot-barycenters
  ☆24Updated 4 years ago