https://github.com/cedrictravelletti/meslas
Learning Excursion Sets of Vector-valued Gaussian Random Fields
https://github.com/cedrictravelletti/meslas
gaussian-processes ocean-sciences
Last synced: 3 months ago
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Learning Excursion Sets of Vector-valued Gaussian Random Fields
- Host: GitHub
- URL: https://github.com/cedrictravelletti/meslas
- Owner: CedricTravelletti
- License: mit
- Created: 2020-06-17T18:32:02.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2023-07-04T07:25:50.000Z (almost 2 years ago)
- Last Synced: 2025-01-23T03:37:37.332Z (5 months ago)
- Topics: gaussian-processes, ocean-sciences
- Language: Python
- Homepage: https://cedrictravelletti.github.io/MESLAS/
- Size: 10.2 MB
- Stars: 0
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# MESLAS: Multivariate Excursion Set Learning by Adaptive Sampling
The MESLAS package provides functionalities for simulation of multivariate
gaussian random fields, as well as adaptive sampling startegies to learn
excursion sets thereof.
It originated as part of a collaboration between NTNU Trondheim and University
of Bern that aimed at developing methods for identification of excursion sets
of vector-valued random fields for applications in autonomous ocean sampling.
More information may be found in the resulting [article](https://arxiv.org/abs/2007.03722).
The package documentation and more details may be found on the [Package Website](https://cedrictravelletti.github.io/MESLAS/).
Cédric Travelletti gratefully acknowledges funding from the **Swiss National Science Fundation
(SNF)** through project no. 178858.