fvGP
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 capabilities for stochastic manifold learning
fvGP holds the world record for exact large-scale Gaussian Processes!
Credits
This code was developed with help from Ron Pandolfi (LBNL), Mark Risser (LBNL), Hengrui Luo (Rice U.), and Vardaan Tekriwal (UCB).
Additional contributions and insights came from across the community, in particular, Kevin Yager, Masafumi Fukuto, and their teams (Brookhaven National Lab).
We acknowledge support from several DOE ASCR, BER, and BES projects, including CAMERA (James Sethian), SPECTRA (Sherry Li), and CASCADE (Bill Collins), as well as support directly from Lawrence Berkeley National Laboratory.
This package uses the HGDL package of David Perryman and Marcus Noack, which is based on the HGDN algorithm by Noack and Funke.
Metadata
Release files for fvgp 4.8.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fvgp-4.8.8.tar.gz | 196.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fvgp-4.8.8-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 363.5 kB
Release files / fvgp-4.8.8.tar.gz
| Download URL | fvgp-4.8.8.tar.gz |
|---|---|
| Size | 196.6 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Release files / fvgp-4.8.8-py3-none-any.whl
| Download URL | fvgp-4.8.8-py3-none-any.whl |
|---|---|
| Size | 166.9 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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