Machine learning for reparameterization of multi-scale closures

Scientific machine learning (ML) is becoming increasingly useful in learning closure models for multi-scale physics problems; however, many ML approaches require a vast array of training data and can struggle with generalization and interpretability. Here, rather than learning an entire closure oper...

Full description

Saved in:
Bibliographic Details
Main Authors: Hilary Egan, Meagan Crowley, Hariswaran Sitaraman, Lila Branchaw, Peter Ciesielski
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Machine Learning: Science and Technology
Subjects:
Online Access:https://doi.org/10.1088/2632-2153/add8de
Tags: Add Tag
No Tags, Be the first to tag this record!