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

• abietti / dpmm
  Variational inference for Dirichlet process mixture models with multinomial mixture components.
  ☆35Updated 11 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆66Updated 2 years ago
• ebonilla / mtgp
  Multi-task Gaussian Process
  ☆43Updated 10 years ago
• SheffieldML / multigp
  Multiple output Gaussian processes in MATLAB including the latent force model.
  ☆51Updated 9 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆63Updated 2 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 8 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
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 3 years ago
• maziarraissi / ParametricGP-in-Matlab
  Parametric Gaussian Process Regression for Big Data (Matlab Version)
  ☆24Updated 7 years ago
• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆93Updated 7 years ago
• Magica-Chen / gptp_multi_output
  multivariate Gaussian process regression and multivariate Student-t process regression
  ☆73Updated 4 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆150Updated 6 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆234Updated 4 years ago
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆32Updated 8 years ago
• markvdw / GPflow-inter-domain
  Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables
  ☆13Updated 7 years ago
• wearepal / UniversalGP
  Generic implementation of GP model
  ☆8Updated 6 years ago
• TENGBINN / Bayes-by-Backprop
  TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper
  ☆51Updated 6 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆121Updated 5 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• aminnayebi / HesBO
  The High-dimensional BayesOpt algorithms from "A Framework for Bayesian Optimization in Embedded Subspaces
  ☆41Updated 6 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 6 years ago
• zi-w / Max-value-Entropy-Search
  Max-value Entropy Search for Efficient Bayesian Optimization
  ☆76Updated 3 years ago
• misokg / NIPS2017
  Multi-Information Source Optimization
  ☆24Updated 6 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆78Updated 5 years ago
• lee813 / pydpmm
  Direct Gibbs sampling for DPMM using python.
  ☆16Updated 8 years ago
• paulorauber / pgm
  Probabilistic graphical models in python
  ☆23Updated 6 years ago
• melihkandemir / atldgp
  Asymmetric Transfer Learning with Deep Gaussian Processes
  ☆18Updated 10 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago