Alternatives and similar repositories for PyVB

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

• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 3 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 10 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆68Updated 7 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 8 years ago
• jluttine / variational-bayes-book
  Open access book on variational Bayesian methods written collaboratively
  ☆28Updated 10 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 11 years ago
• BigBayes / SMS
  Sampling via Moment Sharing
  ☆11Updated 9 years ago
• arahuja / hamiltonian-monte-carlo
  Implementation of Hamiltonian Monte Carlo using Google's TensorFlow
  ☆47Updated 9 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆86Updated 4 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• SheffieldML / vargplvm
  Bayesian GPLVM in MATLAB and R
  ☆75Updated 8 years ago
• yaringal / VSSGP
  Variational Sparse Spectrum Gaussian Process toolkit
  ☆22Updated 10 years ago
• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆93Updated 7 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 7 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• fhuszar / thesis
  my PhD thesis on Bayesian inference
  ☆27Updated 11 years ago
• jhamrick / gaussian_processes
  Python library for working with gaussian processes
  ☆14Updated 11 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆39Updated 9 years ago
• yaringal / CLGP
  Categorical Latent Gaussian Process
  ☆16Updated 10 years ago
• aatapa / RLScore
  ☆68Updated last year
• vsmolyakov / DP_means
  Dirichlet Process K-means
  ☆48Updated last year
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆33Updated 8 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆27Updated 6 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆63Updated 2 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆106Updated 7 years ago
• trungngv / gprn
  Code for the paper 'Efficient Variational Inference for Gaussian Process Regression Networks'
  ☆22Updated 11 years ago
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated last year