Alternatives and similar repositories for dpmm

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

• enalisnick / mixture_density_VAEs
  Variational Autoencoders with Gaussian Mixture Latent Space
  ☆36Updated 7 years ago
• likang7 / variational-dpgmm
  Variational Dirichlet Process Gaussian Mixture Models
  ☆29Updated 10 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 4 years ago
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 8 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• BigBayes / SMS
  Sampling via Moment Sharing
  ☆11Updated 9 years ago
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆29Updated 5 years ago
• lee813 / pydpmm
  Direct Gibbs sampling for DPMM using python.
  ☆16Updated 7 years ago
• mcusi / tf_dpgmm
  Variational inference in Dirichlet process Gaussian mixture model (tensorflow implementation)
  ☆13Updated 6 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
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• zhegan27 / Bayesian_RNN
  The code for the ACL 2017 paper "Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling"
  ☆29Updated 8 years ago
• prasoongoyal / bnp-vae
  ☆11Updated 7 years ago
• bobchennan / VAE_NBP
  Variational Auto-encoder with Non-parametric Bayesian Prior
  ☆43Updated 8 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• enalisnick / stick-breaking_dgms
  Deep Generative Models with Stick-Breaking Priors
  ☆95Updated 8 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆63Updated 2 years ago
• chrisdxie / in-depth-VI-tutorial
  ☆11Updated 8 years ago
• jamesmcinerney / vbmm
  Variational inference for Gaussian mixture models
  ☆35Updated 11 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 7 years ago
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆39Updated 5 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 7 months ago
• rubinxin / FITBO
  Code for Fast Information-theoretic Bayesian Optimisation
  ☆16Updated 6 years ago
• daeilkim / bbvi
  Black Box Variational Inference
  ☆14Updated 9 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 6 years ago
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆18Updated 4 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• sungyubkim / amortized_svgd
  A pytorch implementation of Amortized Stein Variational Gradient Descent/ Stein GAN
  ☆19Updated 6 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
• jiamings / ais
  Annealed Importance Sampling (AIS) for generative models.
  ☆16Updated 6 years ago