Comparison of Gaussian process software: Difference between revisions

Revision as of 23:00, 2 March 2025

Revision as of 13:00, 18 March 2025

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== Comparison table ==

{{sort-under}}

{| class="wikitable sortable sort-under" style="font-size: 90%; text-align: center; width: auto;"

|-

! rowspan="2" | Name

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! colspan="2" | Input

! colspan="2" | Output

! colspan="2" | [[Hyperparameters]]

! colspan="3" | [[Linear transformations]]

! rowspan="2" | Name

|-

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! Approximate

! ND

! {{nowrap}} verth| Non-real}}

! Likelihood

! Errors

! Prior

! Posterior

! {{verth|Derivative}}

! Deriv.

! Finite

! Sum

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! [[scikit-learn]]

|-

! [http://www.cs.toronto.edu/%7Eradford/fbm.software.html fbm]<br/><ref name="vanhatalo2013" />

| {{free}}

| [[C (programming language)|C]]

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! [http://www.cs.toronto.edu/%7Eradford/fbm.software.html fbm]

|-

! [http://www.gaussianprocess.org/gpml/code/matlab/doc/index.html GPML]<br/><ref name="rasmussen2010" /><ref name="vanhatalo2013" />

| {{BSD-lic}}

| [[MATLAB]]

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! [http://www.gaussianprocess.org/gpml/code/matlab/doc/index.html GPML]

|-

! [https://research.cs.aalto.fi/pml/software/gpstuff/ GPstuff]<br/><ref name="vanhatalo2013" />

| {{GPL-lic}}

| [[MATLAB]], [[R (programming language)|R]]

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! [https://research.cs.aalto.fi/pml/software/gpstuff/ GPstuff]

|-

! [https://sheffieldml.github.io/GPy/ GPy]<br/><ref name="matthews2017" />

| {{BSD-lic}}

| [[Python (programming language)|Python]]

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! [https://sheffieldml.github.io/GPy/ GPy]

|-

! [https://www.gpflow.org GPflow]<br/><ref name="matthews2017" />

| {{free|[[Apache License|Apache]]}}

| [[Python (programming language)|Python]]

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! [https://www.gpflow.org GPflow]

|-

! [https://gpytorch.ai GPyTorch]<br/><ref name="gardner2018" />

| {{free|[[MIT License|MIT]]}}

| [[Python (programming language)|Python]]

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! [https://gpytorch.ai GPyTorch]

|-

! [https://CRAN.R-project.org/package=GPvecchia GPvecchia]<br/><ref name="zilber2021" />

| {{GPL-lic}}

| [[R (programming language)|R]]

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! [https://CRAN.R-project.org/package=GPvecchia GPvecchia]

|-

! [https://github.com/marionmari/pyGPs pyGPs]<br/><ref name="neumann2015" />

| {{BSD-lic}}

| [[Python (programming language)|Python]]

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! [https://github.com/marionmari/pyGPs pyGPs]

|-

! [https://CRAN.R-project.org/package=gptk gptk]<br/><ref name="kalaitzis2011" />

| {{BSD-lic}}

| [[R (programming language)|R]]

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! [https://CRAN.R-project.org/package=gptk gptk]

|-

! [https://celerite.readthedocs.io/en/stable/ celerite]<br/><ref name="foreman2017" />

| {{free|[[MIT License|MIT]]}}

| [[Python (programming language)|Python]], [[Julia (programming language)|Julia]], [[C++]]

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! [https://celerite.readthedocs.io/en/stable/ celerite]

|-

! [http://george.readthedocs.io george]<br/><ref name="ambikasaran2016" />

| {{free|[[MIT License|MIT]]}}

| [[Python (programming language)|Python]], [[C++]]

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! [http://george.readthedocs.io george]

|-

! [https://github.com/google/neural-tangents neural-tangents]<br/><ref name="novak2020" />{{efn|neural-tangents is a specialized package for infinitely wide neural networks.}}

| {{free|[[Apache License|Apache]]}}

| [[Python (programming language)|Python]]

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! [https://github.com/google/neural-tangents neural-tangents]

|-

! [https://cran.r-project.org/package=DiceKriging DiceKriging]<br/><ref name="roustant2012" />

| {{GPL-lic}}

| [[R (programming language)|R]]

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! [https://cran.r-project.org/package=DiceKriging DiceKriging]

|-

! [https://openturns.github.io/www/ OpenTURNS]<br/><ref name="baudin2015" />

| {{LGPL-lic}}

| [[Python (programming language)|Python]], [[C++]]

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! [https://openturns.github.io/www/ OpenTURNS]

|-

! [http://www.uqlab.com/ UQLab]<br/><ref name="marelli2014" />

| {{proprietary}}

| [[MATLAB]]

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! [https://celerite2.readthedocs.io/en/latest/ celerite2]

|-

! [https://smt.readthedocs.io/en/latest/ SMT]<br/><ref name="saves2024" /><ref name="bouhlel2019" />

| {{free|[[BSD licenses|BSD]]}}

| [[Python (programming language)|Python]]

| {{yes}}

| {{no}}

| {{yes|Sparse, PODI{{efn|name=PODI| PODI (Proper Orthogonal Decomposition + Interpolation) is an approximation for high-dimensional multioutput regressions. The regression function is lower-dimensional than the outcomes, and the subspace is chosen with the PCA of the (outcome, dependent variable) data. Each principal component is modeled with an a priori independent Gaussian process.<ref name="Porrello24" />}}, other}}

| {{yes|ND}}

| {{no}}

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! [https://github.com/wesselb/stheno Stheno]

|-

! [https://docs.rs/egobox-gp/latest/egobox_gp/ Egobox-gp]<br/><ref name="Lafage2022" />

| {{free|[[Apache License|Apache]]}}

| [[Rust (programming language)|Rust]]

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! Approximate

! ND

! {{nowrap}} verth| Non-real}}

! Likelihood

! Errors

! Prior

! Posterior

! {{verth|Derivative}}

! Deriv.

! Finite

! Sum