Alternatives and similar repositories for PyVB

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

• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 8 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 11 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 4 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆34Updated 10 years ago
• yaringal / VSSGP
  Variational Sparse Spectrum Gaussian Process toolkit
  ☆22Updated 10 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 4 years ago
• jluttine / variational-bayes-book
  Open access book on variational Bayesian methods written collaboratively
  ☆28Updated 10 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆69Updated 8 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆27Updated 6 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆114Updated 12 years ago
• vsmolyakov / DP_means
  Dirichlet Process K-means
  ☆48Updated last year
• jmetzen / sparse-filtering
  Unsupervised feature learning based on sparse-filtering
  ☆55Updated 11 years ago
• locuslab / newton_admm
  A Newton ADMM based solver for Cone programming.
  ☆39Updated 8 years ago
• SheffieldML / vargplvm
  Bayesian GPLVM in MATLAB and R
  ☆75Updated 8 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• izmailovpavel / TTGP
  ☆25Updated 7 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 8 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• wangshusen / RandMatrixMatlab
  simple MATLAB code for randomized matrix computation
  ☆23Updated 9 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆39Updated 9 years ago
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆45Updated 7 years ago
• BigBayes / SMS
  Sampling via Moment Sharing
  ☆11Updated 10 years ago
• trungngv / gprn
  Code for the paper 'Efficient Variational Inference for Gaussian Process Regression Networks'
  ☆22Updated 11 years ago
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆34Updated 8 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• ChunyuanLI / pSGLD
  AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)
  ☆35Updated 7 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆64Updated 6 years ago
• SheffieldML / hgplvm
  Hierarchical Gaussian process latent variable model.
  ☆18Updated 4 years ago