Python package for highly flexible function-valued Gaussian processes (fvGP)

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  • License: GNU General Public License v3 or later (GPLv3+) (*** License Agreement *** GPL v3 License fvGP Copyright (c) 2021, The Regents of the University of...)
  • Author: Marcus Michael Noack
  • Maintainer: Marcus Michael Noack
  • Tags adaptive, autonomous, gui, qt, self driving
  • Requires: Python >=3.9
  • Provides-Extra: docs, plotting, tests
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fvGP

PyPI Documentation Status fvGP CI Codecov PyPI - License DOI

Python package for highly flexible function-valued Gaussian processes (fvGP)

It is recommended to use this package via gpCAM.

Specialties: Extreme-Scale GPs, GPs Tailored for HPC training, Advanced Kernel Designs, Domain-Aware Stochastic Function Approximation Coming soon: All those advancements for stochastic manifold learning

fvGP holds the world record for exact large-scale Gaussian Processes!

Credits

This package uses the HGDL package of David Perryman and Marcus Noack, which is based on the HGDN algorithm by Noack and Funke.

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Avatar for MarcusMichaelNoack from gravatar.com MarcusMichaelNoack Avatar for ronpandolfi from gravatar.com ronpandolfi

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  • License: GNU General Public License v3 or later (GPLv3+) (*** License Agreement *** GPL v3 License fvGP Copyright (c) 2021, The Regents of the University of...)
  • Author: Marcus Michael Noack
  • Maintainer: Marcus Michael Noack
  • Tags adaptive, autonomous, gui, qt, self driving
  • Requires: Python >=3.9
  • Provides-Extra: docs, plotting, tests
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7.4.9 yanked

7.4.8 yanked

4.5.4

4.5.3

4.5.2

4.5.1

4.5.0

4.4.3

4.4.2

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4.3.5

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This version

4.3.3

4.3.2

4.3.1

4.3.0

4.2.14

4.2.13

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2.3.8

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2.3.4

2.3.3

2.3.2

2.3.1

2.3.0

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