Alternatives and similar repositories for Gaussian-Process-Regression-handout

Users that are interested in Gaussian-Process-Regression-handout are comparing it to the libraries listed below

• ebonilla / mtgp
  Multi-task Gaussian Process
  ☆43Updated 10 years ago
• maziarraissi / ParametricGP-in-Matlab
  Parametric Gaussian Process Regression for Big Data (Matlab Version)
  ☆24Updated 7 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆92Updated 3 years ago
• Magica-Chen / gptp_multi_output
  multivariate Gaussian process regression and multivariate Student-t process regression
  ☆73Updated 3 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆44Updated 5 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• SheffieldML / multigp
  Multiple output Gaussian processes in MATLAB including the latent force model.
  ☆50Updated 9 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 7 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆233Updated 4 years ago
• shz9 / csc2541-ml-project
  Modeling Uncertainty in RNNs for Time Series Forecasting
  ☆14Updated 7 years ago
• danilkuzin / GP-EnKF
  Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…
  ☆17Updated 6 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆63Updated 2 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆65Updated 2 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• mcdickenson / em-gaussian
  Python code for Expectation-Maximization estimate of Gaussian mixture model
  ☆76Updated 6 years ago
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆32Updated 8 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆23Updated 9 years ago
• bertini36 / GMM
  Variational Inference in Gaussian Mixture Model
  ☆59Updated 4 years ago
• abietti / dpmm
  Variational inference for Dirichlet process mixture models with multinomial mixture components.
  ☆34Updated 11 years ago
• mebden / GPtutorial
  Matlab code for the introduction to Gaussian processes, 2008
  ☆30Updated 10 years ago
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆49Updated 4 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆150Updated 6 years ago
• wearepal / UniversalGP
  Generic implementation of GP model
  ☆8Updated 6 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆27Updated last year
• shaobohan / VariationalGaussianCopula
  Matlab Code for Variational Gaussian Copula Inference
  ☆16Updated 9 years ago
• lee813 / pydpmm
  Direct Gibbs sampling for DPMM using python.
  ☆16Updated 7 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 6 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆120Updated 5 years ago
• AaltoML / IHGP
  Infinite-horizon Gaussian processes
  ☆32Updated 4 years ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆91Updated 5 years ago