Alternatives and similar repositories for pgds

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

• kzhai / PyNPB
  Non-parametric Bayesian in Python, including Indian buffet process (IBP), hierarchical Dirichlet process (HDP).
  ☆73Updated 9 years ago
• blei-lab / deep-exponential-families
  Deep exponential families (DEFs)
  ☆55Updated 7 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆69Updated 8 years ago
• YingzhenLi / stochastic-EP
  code for stochastic expectation propagation
  ☆16Updated 9 years ago
• aschein / bptf
  Bayesian Poisson tensor factorization
  ☆61Updated 10 months ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• larsmaaloee / auxiliary-deep-generative-models
  Deep generative models for semi-supervised learning.
  ☆109Updated 8 years ago
• tbroderick / streaming_vb
  This is code associated with the paper: Broderick, T, Boyd, N, Wibisono, A, Wilson, AC, and Jordan, MI. Streaming variational Bayes. Neur…
  ☆41Updated 11 years ago
• SheffieldML / deepGPy
  Deep GPs with GPy
  ☆31Updated 9 years ago
• SheffieldML / collab
  Collaborative filtering with the GP-LVM
  ☆25Updated 10 years ago
• zhegan27 / dpfa_icml2015
  The Matlab Code for the ICML 2015 paper "Scalable Deep Poisson Factor Analysis for Topic Modeling"
  ☆19Updated 10 years ago
• edwardlib / papers
  Edward content including papers, posters, and talks
  ☆92Updated 4 years ago
• enalisnick / stick-breaking_dgms
  Deep Generative Models with Stick-Breaking Priors
  ☆96Updated 9 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆106Updated 7 years ago
• rueberger / MJHMC
  Python implementation of Markov Jump Hamiltonian Monte Carlo
  ☆24Updated 8 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 5 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 11 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆64Updated 7 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆83Updated 5 years ago
• HIPS / pgmult
  Dependent multinomials made easy: stick-breaking with the Pólya-gamma augmentation
  ☆61Updated 4 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• mariru / exponential_family_embeddings
  Bernoulli Embeddings for Text
  ☆83Updated 7 years ago
• HIPS / Probabilistic-Backpropagation
  Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
  ☆191Updated 6 years ago
• yburda / iwae
  Code to train Importance Weighted Autoencoders on MNIST and OMNIGLOT
  ☆207Updated 9 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 4 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 years ago
• marcofraccaro / srnn
  Code for "Sequential Neural Models with Stochastic Layers"
  ☆117Updated 8 years ago
• casmls / casmls.github.io
  Columbia Advanced Machine Learning Seminar
  ☆24Updated 7 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 9 years ago
• davidandrzej / PyIBP
  NumPy implementation of infinite latent feature model (aka Indian Buffet Process or IBP)
  ☆49Updated 7 years ago