Alternatives and similar repositories for torch-two-sample

Users that are interested in torch-two-sample are comparing it to the libraries listed below

• amir-abdi / disentanglement-pytorch
  Disentanglement library for PyTorch
  ☆278Updated 3 years ago
• daib13 / TwoStageVAE
  ☆238Updated 6 years ago
• jmtomczak / vae_vampprior
  Code for the paper "VAE with a VampPrior", J.M. Tomczak & M. Welling
  ☆228Updated 7 years ago
• iffsid / disentangling-disentanglement
  ☆91Updated 6 years ago
• riannevdberg / sylvester-flows
  ☆180Updated 5 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 5 years ago
• loeweX / Greedy_InfoMax
  Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations
  ☆285Updated 2 years ago
• rtqichen / residual-flows
  code for "Residual Flows for Invertible Generative Modeling".
  ☆271Updated last year
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• senya-ashukha / real-nvp-pytorch
  Real NVP PyTorch a Minimal Working Example | Normalizing Flow
  ☆139Updated 4 years ago
• rtqichen / beta-tcvae
  code for "Isolating Sources of Disentanglement in Variational Autoencoders".
  ☆350Updated 2 years ago
• wgrathwohl / JEM
  Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"
  ☆423Updated 2 years ago
• nicola-decao / BNAF
  Pytorch implementation of Block Neural Autoregressive Flow
  ☆179Updated 3 years ago
• pluskid / fitting-random-labels
  Example code for the paper "Understanding deep learning requires rethinking generalization"
  ☆178Updated 5 years ago
• cianeastwood / qedr
  Quantitative evaluation of disentangled representations
  ☆62Updated 7 years ago
• didriknielsen / survae_flows
  Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"
  ☆287Updated 4 years ago
• Schlumberger / joint-vae
  Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation
  ☆465Updated 6 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆230Updated 3 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 / acai
  Code for "Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer"
  ☆244Updated 6 years ago
• y0ast / Glow-PyTorch
  Simple, extendable, easy to understand Glow implementation in PyTorch
  ☆384Updated 2 years ago
• fpcasale / GPPVAE
  Gaussian Process Prior Variational Autoencoder
  ☆84Updated 6 years ago
• PolinaKirichenko / flows_ood
  ☆87Updated 3 years ago
• ctallec / pyvarinf
  Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
  ☆359Updated 5 years ago
• ikostrikov / pytorch-flows
  PyTorch implementations of algorithms for density estimation
  ☆585Updated 4 years ago
• j-min / Dropouts
  PyTorch Implementations of Dropout Variants
  ☆87Updated 7 years ago
• ritheshkumar95 / energy_based_generative_models
  PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models
  ☆151Updated 5 years ago
• nicola-decao / s-vae-pytorch
  Pytorch implementation of Hyperspherical Variational Auto-Encoders
  ☆369Updated 5 years ago
• djsutherland / opt-mmd
  Learning kernels to maximize the power of MMD tests
  ☆210Updated 7 years ago
• ShengjiaZhao / MMD-Variational-Autoencoder
  ☆109Updated 7 years ago