Alternatives and similar repositories for notebook:

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

• jamesrobertlloyd / gpss-research
  Kernel structure discovery research code - likely to be unstable
  ☆189Updated 9 years ago
• jamesrobertlloyd / gp-structure-search
  ☆232Updated 7 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
  ☆183Updated 10 years ago
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated 8 months ago
• mwhoffman / pybo
  Python package for modular Bayesian optimization
  ☆134Updated 4 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆91Updated 3 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆84Updated 3 years ago
• sods / paramz
  Parameterization Framework for parameterized model creation and handling.
  ☆49Updated last month
• GPflow / GPflowOpt
  Bayesian Optimization using GPflow
  ☆271Updated 4 years ago
• jameshensman / GPclust
  Clustering time series using Gaussian processes and Variational Bayes.
  ☆39Updated 4 years ago
• dfm / gp
  A tutorial about Gaussian process regression
  ☆185Updated 4 years ago
• powerscorinne / GLRM
  ☆98Updated 7 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated 7 months ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated 7 months ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 7 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 / PyDeepGP
  Deep Gaussian Processes in Python
  ☆233Updated 3 years ago
• twiecki / WhileMyMCMCGentlySamples
  my blog
  ☆266Updated 2 years ago
• lmc2179 / bayesian_bootstrap
  bayesian bootstrapping in python
  ☆121Updated 3 years ago
• gradientinstitute / aboleth
  A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation
  ☆128Updated 3 years ago
• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆114Updated 11 years ago
• PMBio / pygp
  A Gaussian process toolbox in python
  ☆42Updated 12 years ago
• eth-cscs / abcpy
  ABCpy package
  ☆113Updated 10 months ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 7 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆149Updated 6 years ago
• slinderman / pypolyagamma
  Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.
  ☆82Updated 4 years ago
• markvdw / GParML
  Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.
  ☆43Updated 11 years ago
• elfi-dev / elfi
  ELFI - Engine for Likelihood-Free Inference
  ☆272Updated 8 months ago
• ronojoy / pylearn
  Bayesian machine learning in Python
  ☆76Updated 9 years ago
• rcmorehead / simpleabc
  A Python package for Approximate Bayesian Computation
  ☆36Updated 8 years ago