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  • spBayes
  • Referenced in 339 articles [sw10160]
  • template encompassing a wide variety of Gaussian spatial process models for univariate as well...

  • Kernlab
  • Referenced in 93 articles [sw07926]
  • Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver...

  • SPOT

  • Referenced in 87 articles [sw06347]
  • such as CART and random forest; Gaussian process models (Kriging), and combinations of di erent...

  • ParEGO
  • Referenced in 58 articles [sw10968]
  • latin hypercube and updates a Gaussian processes surrogate model of the search landscape after every...

  • tgp
  • Referenced in 39 articles [sw07921]
  • package tgp: Bayesian treed Gaussian process models. Bayesian nonstationary, semiparametric nonlinear regression and design ... treed Gaussian processes (GPs) with jumps to the limiting linear model (LLM). Special cases also...

  • GPML
  • Referenced in 38 articles [sw12890]
  • Gaussian processes for machine learning (GPML) toolbox. The GPML toolbox provides a wide range ... functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance ... ones. Several likelihood functions are supported including Gaussian and heavy-tailed for regression as well...

  • invGauss
  • Referenced in 122 articles [sw11207]
  • data. invGauss fits the (randomized drift) inverse Gaussian distribution to survival data. The model ... Survival and Event History Analysis. A Process Point of View. Springer, 2008. It is based ... Wiener process, where drift towards the barrier has been randomized with a Gaussian distribution...

  • GPy
  • Referenced in 29 articles [sw14302]
  • Gaussian Process (GP) framework written in python, from the Sheffield machine learning group. Gaussian processes...

  • UQLab
  • Referenced in 33 articles [sw19740]
  • members, e.g. metamodeling (polynomial chaos expansions, Gaussian process modelling, a.k.a. Kriging, low-rank tensor approximations...

  • GPfit
  • Referenced in 19 articles [sw14044]
  • package GPfit: Gaussian Processes Modeling. A computationally stable approach of fitting a Gaussian Process ... model to a deterministic simulator. Gaussian process (GP) models are commonly used statistical metamodels...

  • George
  • Referenced in 20 articles [sw29786]
  • fast and flexible Python library for Gaussian Process (GP) Regression. A full introduction ... theory of Gaussian Processes is beyond the scope of this documentation but the best resource...

  • INLA
  • Referenced in 40 articles [sw07535]
  • toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA). This ... models that are based on log-Gaussian Cox processes and include local interaction in these...

  • LS-SVMlab
  • Referenced in 26 articles [sw07367]
  • closely related to regularization networks and Gaussian processes but additionally emphasize and exploit primal-dual...

  • mlegp
  • Referenced in 17 articles [sw08213]
  • package mlegp: Maximum Likelihood Estimates of Gaussian Processes. Maximum likelihood Gaussian process modeling for univariate...

  • GPstuff
  • Referenced in 23 articles [sw12867]
  • toolbox is a versatile collection of Gaussian process models and computational tools required for inference...

  • GPS-ABC
  • Referenced in 16 articles [sw16117]
  • Gaussian Process Surrogate Approximate Bayesian Computation. Scientists often express their understanding of the world through ... obtained from every simulation in a Gaussian process which acts as a surrogate function...

  • OP-ELM
  • Referenced in 22 articles [sw12171]
  • support vector machine (SVM), and Gaussian process (GP). As the experiments for both regression...

  • laGP
  • Referenced in 21 articles [sw14043]
  • laGP: Local Approximate Gaussian Process Regression. Performs approximate GP regression for large computer experiments...

  • spTimer
  • Referenced in 16 articles [sw24237]
  • space-time data using [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian Auto-Regressive ... Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based AR Models for spatio-temporal...

  • GPflow
  • Referenced in 14 articles [sw21518]
  • GPflow: a Gaussian process library using tensorflow. GPflow is a Gaussian process library that uses...