PIED: Physics-Informed Experimental Design for Inverse Problems

Fuente: arXiv

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Bibliographic Details
Main Authors:	Hemachandra, Apivich, Lau, Gregory Kang Ruey, Ng, See-Kiong, Low, Bryan Kian Hsiang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Computational Physics Data Analysis, Statistics and Probability
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2503.07070