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

Project description

fvGP

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

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

Credits

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

======= History

0.1.0 (2020-08-07)

  • First release on PyPI.

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This version

3.3.8

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