Alternatives and similar repositories for gp-structure-search

Users that are interested in gp-structure-search are comparing it to the libraries listed below

• jamesrobertlloyd / gpss-research
  Kernel structure discovery research code - likely to be unstable
  ☆191Updated 10 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 11 years ago
• GPflow / GPflowOpt
  Bayesian Optimization using GPflow
  ☆271Updated 4 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆234Updated 4 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆150Updated 6 years ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated last year
• dfm / gp
  A tutorial about Gaussian process regression
  ☆188Updated 4 years ago
• SheffieldML / notebook
  Collection of jupyter notebooks for demonstrating software.
  ☆169Updated 2 years ago
• elfi-dev / elfi
  ELFI - Engine for Likelihood-Free Inference
  ☆277Updated 3 months ago
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆216Updated 6 years ago
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated last year
• mcleonard / sampyl
  MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice
  ☆339Updated 2 years ago
• vlad17 / runlmc
  Structurally efficient multi-output linearly coregionalized Gaussian Processes: it's tricky, tricky, tricky, tricky, tricky.
  ☆38Updated 2 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated 10 months ago
• wujian16 / Cornell-MOE
  A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
  ☆268Updated 5 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆106Updated 7 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 3 years ago
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆33Updated 8 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated last year
• dilinwang820 / Stein-Variational-Gradient-Descent
  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
  ☆407Updated last year
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 4 years ago
• ColCarroll / minimc
  Just a little MCMC
  ☆228Updated last year
• jmetzen / bayesian_optimization
  Bayesian optimization
  ☆38Updated 5 years ago
• dfm / george
  Fast and flexible Gaussian Process regression in Python
  ☆459Updated this week
• clinicalml / structuredinference
  Structured Inference Networks for Nonlinear State Space Models
  ☆274Updated 7 years ago
• pyprob / pyprob
  A probabilistic programming system for simulators and high-performance computing (HPC), based on PyTorch
  ☆389Updated last year
• josejimenezluna / pyGPGO
  Bayesian optimization for Python
  ☆246Updated 3 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 years ago
• HIPS / Probabilistic-Backpropagation
  Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
  ☆192Updated 6 years ago
• mfouesneau / NUTS
  python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011
  ☆132Updated 4 years ago