• tgp

  • Referenced in 35 articles [sw07921]
  • Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes (GPs) with jumps...
  • laGP

  • Referenced in 20 articles [sw14043]
  • laGP: Local Approximate Gaussian Process Regression. Performs approximate GP regression for large computer experiments...
  • GPML

  • Referenced in 37 articles [sw12890]
  • wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified ... functions are supported including Gaussian and heavy-tailed for regression as well as others suitable...
  • Kernlab

  • Referenced in 88 articles [sw07926]
  • classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab includes ... Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver...
  • George

  • Referenced in 16 articles [sw29786]
  • flexible Python library for Gaussian Process (GP) Regression. A full introduction to the theory...
  • invGauss

  • Referenced in 114 articles [sw11207]
  • invGauss: Threshold regression that fits the (randomized drift) inverse Gaussian distribution to survival data. invGauss ... fits the (randomized drift) inverse Gaussian distribution to survival data. The model is described ... Survival and Event History Analysis. A Process Point of View. Springer, 2008. It is based...
  • acebayes

  • Referenced in 11 articles [sw20243]
  • optimisation steps. At each step, a Gaussian process regression model is used to approximate...
  • SPOT

  • Referenced in 76 articles [sw06347]
  • includes methods for tuning based on classical regression and analysis of variance techniques; tree-based ... such as CART and random forest; Gaussian process models (Kriging), and combinations of di erent...
  • spTimer

  • Referenced in 15 articles [sw24237]
  • using [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian Auto-Regressive (AR) Models...
  • gprege

  • Referenced in 6 articles [sw31093]
  • expressed gene expression time-courses through Gaussian process regression”. The software fits two GPs with...
  • OP-ELM

  • Referenced in 22 articles [sw12171]
  • detail and then applied to several regression and classification problems. Results for both computational time ... machine (SVM), and Gaussian process (GP). As the experiments for both regression and classification illustrate...
  • gptk

  • Referenced in 5 articles [sw24250]
  • implements a general-purpose toolkit for Gaussian process regression with a variety of covariance functions...
  • lineqGPR

  • Referenced in 2 articles [sw31421]
  • package lineqGPR: Gaussian Process Regression Models with Linear Inequality Constraints. Gaussian processes regression models with...
  • GPareto

  • Referenced in 3 articles [sw28711]
  • Pareto Front Estimation and Optimization. Gaussian process regression models, a.k.a. Kriging models, are applied...
  • GPFDA

  • Referenced in 6 articles [sw14770]
  • analysis. Use functional regression as the mean structure and Gaussian Process as the covariance structure...
  • muq

  • Referenced in 2 articles [sw33064]
  • internally and through NLOPT); Regression (including Gaussian process regression...
  • GPLP

  • Referenced in 1 article [sw08483]
  • local and parallel computation toolbox for Gaussian process regression. This paper presents the getting-started ... local and parallel computation toolbox for Gaussian process regression (GPLP), an open source software package...
  • spNNGP

  • Referenced in 3 articles [sw31449]
  • Datasets using Nearest Neighbor Gaussian Processes. Fits univariate Bayesian spatial regression models for large datasets...
  • GoGP

  • Referenced in 1 article [sw23912]
  • GoGP: Fast Online Regression with Gaussian Processes ... most current challenging problems in Gaussian process regression (GPR) is to handle large-scale datasets ... paper, we introduce a novel online Gaussian process model that could scale with massive datasets ... based on alternative representation of the Gaussian process under geometric and optimization views, hence termed...
  • krisp

  • Referenced in 1 article [sw14717]
  • kriging based regression (also known as Gaussian process regression) and optimization of deterministic simulators...