Alternatives and similar repositories for pyblr:

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

• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆66Updated 7 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆92Updated 3 years ago
• YingzhenLi / stochastic-EP
  code for stochastic expectation propagation
  ☆16Updated 9 years ago
• bstriner / bayesian_dense
  Bayesian Weight Uncertainty Dense Layer for Keras
  ☆48Updated 8 years ago
• taku-y / pymc3
  Probabilistic Programming in Python. Uses Theano as a backend and includes the NUTS sampler.
  ☆12Updated 7 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 7 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 9 years ago
• kuleshov / online-learning
  A few basic online learning algorithms
  ☆24Updated 3 years ago
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆44Updated 7 years ago
• jluttine / variational-bayes-book
  Open access book on variational Bayesian methods written collaboratively
  ☆28Updated 9 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• muupan / deep-ensemble-uncertainty
  An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)
  ☆34Updated 8 years ago
• automl / pysmac
  simple python interface to SMAC.
  ☆21Updated 7 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆84Updated 3 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• arahuja / hamiltonian-monte-carlo
  Implementation of Hamiltonian Monte Carlo using Google's TensorFlow
  ☆47Updated 9 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆96Updated 7 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 7 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 6 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• cangermueller / ppca
  Probabilistic Principal Component Analysis
  ☆61Updated 7 years ago
• DanielTakeshi / MCMC_and_Dynamics
  Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)
  ☆42Updated 5 years ago
• nitromannitol / stochastic-quasi-newton
  modular implementation of new algorithm
  ☆13Updated 10 years ago
• tabacof / bayesian-nn-uncertainty
  Classification uncertainty using Bayesian neural networks
  ☆33Updated 8 years ago
• robertnishihara / gess
  An MCMC algorithm for sampling continuous probability distributions in parallel
  ☆19Updated 10 years ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 5 years ago
• achab / nphc
  NPHC
  ☆17Updated 3 years ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 7 years ago