The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/edd6a7d5-2d9d-4b51-81d2-7c1b234431d6

Yang, Maosheng (2025): Code underlying: Hodge-Compositional Edge Gaussian Processes. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/edd6a7d5-2d9d-4b51-81d2-7c1b234431d6.v1

Categories

• Artificial Intelligence and Image Processing
• Information and Computing Sciences

Keywords

edge space forex Gaussian process Hodge theorem ocean currents

Licence

CC BY 4.0

Interoperability

• RO-Crate Metadata

Collection

• Code underlying 4 publications on Learning on Simplicial Complexes

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by Maosheng Yang

This implements the Gaussian processes on the edge space of a simplicial 2-complex, including applications in forex prediction, ocean current interpolation and water networks state estimation. Our way of constructing the edge Gaussian processes allows separate modeling of the different parts of the edge signals, e.g., divergence-free part or curl-free part. This code shows how we can use Gaussian process regression to interpolate or predict signals on the edge space while respecting their intrinsic properties.

History

• 2025-05-26 first online, published, posted

Publisher

4TU.ResearchData

Format

script/.ipynb, script/.py

Associated peer-reviewed publication

Hodge-Compositional Edge Gaussian Processes

Code hosting project url

https://github.com/cookbook-ms/Hodge-Edge-GP