Alternatives and similar repositories for wasserstein-dist

Users that are interested in wasserstein-dist are comparing it to the libraries listed below

• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆90Updated 7 years ago
• skolouri / swgmm
  Sliced Wasserstein Distance for Learning Gaussian Mixture Models
  ☆66Updated 2 years ago
• mducoffe / Learning-Wasserstein-Embeddings
  Keras implementation of Deep Wasserstein Embeddings
  ☆48Updated 7 years ago
• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆102Updated 6 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
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆80Updated 6 years ago
• maremun / swg
  Sliced Wasserstein Generator
  ☆23Updated 6 years ago
• vincentherrmann / wasserstein-notebook
  Wasserstein / earth mover's distance visualizations
  ☆66Updated 8 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
• aditya-grover / uae
  Uncertainty Autoencoders, AISTATS 2019
  ☆56Updated 6 years ago
• LuisArmandoPerez / DiffusionVAE
  ☆29Updated 3 years ago
• geniki / neural-processes
  PyTorch implementation of Neural Processes
  ☆89Updated 6 years ago
• kefirski / variational_dropout
  Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
  ☆49Updated 7 years ago
• nicola-decao / s-vae-tf
  Tensorflow implementation of Hyperspherical Variational Auto-Encoders
  ☆233Updated 6 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
• yaohungt / Adaptive-Regularization-Neural-Network
  [NeurIPS'19] [PyTorch] Adaptive Regularization in NN
  ☆68Updated 5 years ago
• ucla-vision / entropy-sgd
  Lua implementation of Entropy-SGD
  ☆82Updated 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
• mctorch / mctorch
  A manifold optimization library for deep learning
  ☆249Updated 4 years ago
• mzgubic / MINE
  Mutual Information Neural Estimator implemented in Tensorflow
  ☆46Updated 6 years ago
• asteroidhouse / self-tuning-networks
  Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088
  ☆54Updated 6 years ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆112Updated 6 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• jayanthkoushik / torch-gel
  Group elastic net implementation in PyTorch.
  ☆45Updated 4 years ago
• mgermain / MADE
  MADE: Masked Autoencoder for Distribution Estimation
  ☆102Updated 5 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 5 years ago
• wlwkgus / DeepSpectralClustering
  Pytorch Implemention of paper "Deep Spectral Clustering Learning", the state of the art of the Deep Metric Learning Paper
  ☆93Updated 7 years ago
• pbrakel / anica
  Adversarial Non-linear Independent Component Analysis
  ☆50Updated 7 years ago
• lixilinx / psgd_tf
  Tensorflow implementation of preconditioned stochastic gradient descent
  ☆34Updated last year
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated 11 months ago