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spBayes
- Referenced in 365 articles
[sw10160]
- template encompassing a wide variety of Gaussian spatial process models for univariate as well...
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Kernlab
- Referenced in 103 articles
[sw07926]
- Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver...
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SPOT
- Referenced in 87 articles
[sw06347]
- such as CART and random forest; Gaussian process models (Kriging), and combinations of di erent...
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ParEGO
- Referenced in 60 articles
[sw10968]
- latin hypercube and updates a Gaussian processes surrogate model of the search landscape after every...
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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...
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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...
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GPy
- Referenced in 32 articles
[sw14302]
- Gaussian Process (GP) framework written in python, from the Sheffield machine learning group. Gaussian processes...
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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...
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UQLab
- Referenced in 41 articles
[sw19740]
- members, e.g. metamodeling (polynomial chaos expansions, Gaussian process modelling, a.k.a. Kriging, low-rank tensor approximations...
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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...
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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...
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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...
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mlegp
- Referenced in 20 articles
[sw08213]
- package mlegp: Maximum Likelihood Estimates of Gaussian Processes. Maximum likelihood Gaussian process modeling for univariate...
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GPflow
- Referenced in 19 articles
[sw21518]
- GPflow: a Gaussian process library using tensorflow. GPflow is a Gaussian process library that uses...
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laGP
- Referenced in 27 articles
[sw14043]
- laGP: Local Approximate Gaussian Process Regression. Performs approximate GP regression for large computer experiments...
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LS-SVMlab
- Referenced in 26 articles
[sw07367]
- closely related to regularization networks and Gaussian processes but additionally emphasize and exploit primal-dual...
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GPvecchia
- Referenced in 17 articles
[sw41328]
- package GPvecchia: Scalable Gaussian-Process Approximations. Fast scalable Gaussian process approximations, particularly well suited...
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GPstuff
- Referenced in 24 articles
[sw12867]
- toolbox is a versatile collection of Gaussian process models and computational tools required for inference...
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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...
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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...