Alternatives and similar repositories for vbmm:

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

• enalisnick / stick-breaking_dgms
  Deep Generative Models with Stick-Breaking Priors
  ☆95Updated 8 years ago
• marcofraccaro / srnn
  Code for "Sequential Neural Models with Stochastic Layers"
  ☆117Updated 8 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• AMLab-Amsterdam / SEVDL_MGP
  Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…
  ☆30Updated 4 years ago
• casperkaae / LVAE
  Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"
  ☆101Updated 9 years ago
• YingzhenLi / vae_renyi_divergence
  A tensorflow implementation of VAE training with Renyi divergence
  ☆31Updated 8 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 4 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 8 years ago
• zhegan27 / dpfa_icml2015
  The Matlab Code for the ICML 2015 paper "Scalable Deep Poisson Factor Analysis for Topic Modeling"
  ☆19Updated 9 years ago
• larsmaaloee / auxiliary-deep-generative-models
  Deep generative models for semi-supervised learning.
  ☆108Updated 8 years ago
• mgermain / MADE
  MADE: Masked Autoencoder for Distribution Estimation
  ☆102Updated 4 years ago
• DartML / SteinGAN
  code for steinGAN - Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning
  ☆27Updated 6 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 8 years ago
• ChunyuanLI / pSGLD
  AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)
  ☆35Updated 6 years ago
• enalisnick / mixture_density_VAEs
  Variational Autoencoders with Gaussian Mixture Latent Space
  ☆36Updated 7 years ago
• daeilkim / bbvi
  Black Box Variational Inference
  ☆14Updated 9 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• YingzhenLi / stochastic-EP
  code for stochastic expectation propagation
  ☆16Updated 9 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• kefirski / bdir_vae
  simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch
  ☆52Updated 7 years ago
• phreeza / tensorflow-vrnn
  A variational recurrent neural network implementation in tensorflow
  ☆103Updated 7 years ago
• RuiShu / vae-experiments
  Code for some of the experiments I did with variational autoencoders on multi-modality and atari video prediction. Atari video prediction…
  ☆62Updated 8 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆96Updated 7 years ago
• blei-lab / deep-exponential-families
  Deep exponential families (DEFs)
  ☆55Updated 7 years ago
• sordonia / zforcing
  ZForcing Repo
  ☆40Updated 7 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago