Alternatives and similar repositories for LVAE

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

• bfarzin / pytorch_aae
  Pytorch Adversarial Auto Encoder (AAE)
  ☆87Updated 6 years ago
• mducoffe / Learning-Wasserstein-Embeddings
  Keras implementation of Deep Wasserstein Embeddings
  ☆48Updated 7 years ago
• ritheshkumar95 / energy_based_generative_models
  PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models
  ☆153Updated 5 years ago
• iffsid / disentangling-disentanglement
  ☆91Updated 6 years ago
• weixsong / NormalizingFlow
  Implementation of different Normalizing Flows, NF, Planar Flows, IAF, etc.
  ☆29Updated 7 years ago
• maremun / swg
  Sliced Wasserstein Generator
  ☆23Updated 6 years ago
• dilinwang820 / nonlinear_svgd
  Nonlinear SVGD for Learning Diversified Mixture Models
  ☆13Updated 6 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆90Updated 7 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆35Updated 5 years ago
• 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
• MichaelArbel / Scaled-MMD-GAN
  Scaled MMD GAN
  ☆36Updated 5 years ago
• RobRomijnders / bayes_nn
  Uncertainty interpretations of the neural network
  ☆32Updated 7 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆42Updated 5 years ago
• ashwindcruz / dgm
  Deep Generative Models (Chainer)
  ☆10Updated 7 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆56Updated 3 years ago
• dcmoyer / inv-rep
  Code for Invariant Rep. Without Adversaries (NIPS 2018)
  ☆35Updated 5 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
• KyleGoyette / nnRNN
  ☆24Updated 5 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 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
• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆103Updated 6 years ago
• larsmaaloee / BIVA
  BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling
  ☆29Updated 5 years ago
• sajadn / Exemplar-VAE
  Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation
  ☆68Updated 4 years ago
• conormdurkan / neural-statistician
  PyTorch Implementation of Neural Statistician
  ☆60Updated 3 years ago
• maitek / waae-pytorch
  Wasserstein Adversarial Autoencoder Pytorch
  ☆27Updated 7 years ago
• mzgubic / MINE
  Mutual Information Neural Estimator implemented in Tensorflow
  ☆46Updated 6 years ago