Alternatives and similar repositories for GPz

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

• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆68Updated 3 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆31Updated 2 years ago
• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆176Updated 4 months ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆53Updated 5 years ago
• LiuHaiTao01 / SVSHGP
  Stochastic variational heteroscedastic Gaussian process
  ☆15Updated 6 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆236Updated 4 years ago
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆34Updated 8 years ago
• mfouesneau / NUTS
  python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011
  ☆132Updated 4 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated 11 months ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆68Updated 8 months ago
• dfm / gp
  A tutorial about Gaussian process regression
  ☆189Updated 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
  ☆186Updated 11 years ago
• dflemin3 / approxposterior
  A Python package for approximate Bayesian inference and optimization using Gaussian processes
  ☆42Updated last year
• pmelchior / proxmin
  Proximal optimization in pure python
  ☆118Updated 3 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• Gabriel-p / pythonMCMC
  A list of Python-based MCMC & ABC packages
  ☆123Updated 3 months ago
• lzkelley / kalepy
  Kernel Density Estimation and (re)sampling
  ☆62Updated 2 years ago
• aboustati / dgplib
  Library for Deep Gaussian Processes based on GPflow
  ☆19Updated 5 years ago
• zi-w / Max-value-Entropy-Search
  Max-value Entropy Search for Efficient Bayesian Optimization
  ☆78Updated 3 years ago
• alshedivat / gpml
  An up-to-date version of GPML library.
  ☆37Updated 6 years ago
• SheffieldML / multigp
  Multiple output Gaussian processes in MATLAB including the latent force model.
  ☆51Updated 9 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆25Updated 9 years ago
• AaltoML / hilbert-gp
  Codes for Hilbert space reduced-rank GP regression
  ☆14Updated 6 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• erichanslee / GP_Derivatives
  Scalable Gaussian Process Regression with Derivatives
  ☆38Updated 6 years ago
• Magica-Chen / gptp_multi_output
  multivariate Gaussian process regression and multivariate Student-t process regression
  ☆75Updated 4 years ago
• matt-graham / mici
  Manifold Markov chain Monte Carlo methods in Python
  ☆233Updated 3 weeks ago
• AaltoML / BayesNewton
  Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
  ☆237Updated last year
• jejjohnson / uncertain_gps
  Exploring how to to deal with uncertain inputs with gaussian process regression models.
  ☆27Updated 4 years ago