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