Numerical linear algebra with ML for coastal oceanography
Dnr:
NAISS 2025/22-762
Type:
NAISS Small Compute
Principal Investigator:
Elias Jarlebring
Affiliation:
Kungliga Tekniska högskolan
Start Date:
2025-05-15
End Date:
2026-06-01
Primary Classification:
10105: Computational Mathematics
Webpage:
Allocation
Abstract
This project concerns the use of certain numerical linear algbera techniques combined with ML applied to data from coastal oceanography. More precisely, we plan to use graph neural networks on drifter data to both predict and train models. The project is joint within SeRC.