Alternatives and similar repositories for gp_extras

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

• jmetzen / bayesian_optimization
  Bayesian optimization
  ☆37Updated 5 years ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated 10 months ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 3 years ago
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆214Updated 6 years ago
• SheffieldML / notebook
  Collection of jupyter notebooks for demonstrating software.
  ☆167Updated 2 years ago
• sods / paramz
  Parameterization Framework for parameterized model creation and handling.
  ☆49Updated 4 months ago
• jamesrobertlloyd / gpss-research
  Kernel structure discovery research code - likely to be unstable
  ☆190Updated 9 years ago
• jamesrobertlloyd / gp-structure-search
  ☆233Updated 7 years ago
• gpapamak / epsilon_free_inference
  Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"
  ☆31Updated 5 years ago
• duvenaud / phd-thesis
  I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth
  ☆185Updated 10 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆26Updated 5 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆82Updated 5 years ago
• mwhoffman / pybo
  Python package for modular Bayesian optimization
  ☆135Updated 4 years ago
• PMBio / pygp
  A Gaussian process toolbox in python
  ☆42Updated 13 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated 10 months ago
• elfi-dev / elfi
  ELFI - Engine for Likelihood-Free Inference
  ☆275Updated 3 weeks ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• powerscorinne / GLRM
  ☆98Updated 7 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆96Updated 7 years ago
• robertnishihara / gess
  An MCMC algorithm for sampling continuous probability distributions in parallel
  ☆19Updated 10 years ago
• vlad17 / runlmc
  Structurally efficient multi-output linearly coregionalized Gaussian Processes: it's tricky, tricky, tricky, tricky, tricky.
  ☆38Updated 2 years ago
• dfm / gp
  A tutorial about Gaussian process regression
  ☆188Updated 4 years ago
• SheffieldML / deepGPy
  Deep GPs with GPy
  ☆31Updated 9 years ago
• dfm / george
  Fast and flexible Gaussian Process regression in Python
  ☆459Updated last month
• jameshensman / GPclust
  Clustering time series using Gaussian processes and Variational Bayes.
  ☆39Updated 5 years ago
• eth-cscs / abcpy
  ABCpy package
  ☆114Updated last year
• ColCarroll / minimc
  Just a little MCMC
  ☆227Updated 11 months ago
• wujian16 / Cornell-MOE
  A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
  ☆269Updated 5 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 6 years ago
• izmailovpavel / TTGP
  ☆26Updated 7 years ago