Alternatives and similar repositories for Correlated-VAEs

Users that are interested in Correlated-VAEs are comparing it to the libraries listed below

• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• geosada / LVAE
  LVAE: Ladder Variational Auto-Encoders (NIPS 2016) with TensorFlow.
  ☆16Updated 7 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• MichaelArbel / Scaled-MMD-GAN
  Scaled MMD GAN
  ☆36Updated 5 years ago
• YingzhenLi / VRbound
  code release for the NIPS 2016 paper
  ☆27Updated 8 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 years ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 6 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆46Updated 7 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 10 months ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• mducoffe / Learning-Wasserstein-Embeddings
  Keras implementation of Deep Wasserstein Embeddings
  ☆48Updated 7 years ago
• vodp / py-kmm
  A Python implementation of Kernel Mean Matching data reweighting algorithm
  ☆33Updated 9 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• paruby / Wasserstein-Auto-Encoders
  Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761
  ☆37Updated 7 years ago
• USC-Melady / KDD19-CoSTCo
  ☆22Updated 2 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
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• dimkal89 / rvae
  ☆38Updated 5 years ago
• cambridge-mlg / SPVAE
  Tensorflow code for "Hierarchical Decompositional Mixtures of Variational Autoencoders" (ICML'19)
  ☆12Updated 5 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 8 years ago
• keyonvafa / logistic-reg-bbvi-blog
  Black Box Variational Inference for Bayesian logistic regression
  ☆18Updated 8 years ago
• emreaksan / stcn
  STCN: Stochastic Temporal Convolutional Networks
  ☆69Updated 5 years ago
• wilson-ye-chen / sp-mcmc
  MATLAB code for Stein Point Markov Chain Monte Carlo.
  ☆13Updated 6 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆90Updated 7 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆56Updated 3 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆36Updated 5 years ago
• bfarzin / pytorch_aae
  Pytorch Adversarial Auto Encoder (AAE)
  ☆87Updated 6 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago