• spBayes

• Referenced in 365 articles [sw10160]
• template encompassing a wide variety of Gaussian spatial process models for univariate as well...

• Kernlab

• Referenced in 103 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 60 articles [sw10968]
• latin hypercube and updates a Gaussian processes surrogate model of the search landscape after every...

• GPML

• Referenced in 42 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...

• tgp

• Referenced in 41 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...

• GPy

• Referenced in 32 articles [sw14302]
• Gaussian Process (GP) framework written in python, from the Sheffield machine learning group. Gaussian processes...

• invGauss

• Referenced in 128 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...

• UQLab

• Referenced in 41 articles [sw19740]
• members, e.g. metamodeling (polynomial chaos expansions, Gaussian process modelling, a.k.a. Kriging, low-rank tensor approximations...

• George

• Referenced in 26 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...

• GPfit

• Referenced in 20 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...

• INLA

• Referenced in 47 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...

• mlegp

• Referenced in 20 articles [sw08213]
• package mlegp: Maximum Likelihood Estimates of Gaussian Processes. Maximum likelihood Gaussian process modeling for univariate...

• GPflow

• Referenced in 19 articles [sw21518]
• GPflow: a Gaussian process library using tensorflow. GPflow is a Gaussian process library that uses...

• laGP

• Referenced in 27 articles [sw14043]
• laGP: Local Approximate Gaussian Process Regression. Performs approximate GP regression for large computer experiments...

• LS-SVMlab

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

• GPvecchia

• Referenced in 17 articles [sw41328]
• package GPvecchia: Scalable Gaussian-Process Approximations. Fast scalable Gaussian process approximations, particularly well suited...

• GPstuff

• Referenced in 24 articles [sw12867]
• toolbox is a versatile collection of Gaussian process models and computational tools required for inference...

• GPS-ABC

• Referenced in 17 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...

• spTimer

• Referenced in 18 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...