PIED: Physics-Informed Experimental Design for Inverse Problems

Apivich Hemachandra; Gregory Kang Ruey Lau; See-Kiong Ng; Bryan Kian Hsiang Low

PIED: Physics-Informed Experimental Design for Inverse Problems

Apivich Hemachandra, Gregory Kang Ruey Lau, See-Kiong Ng, Bryan Kian Hsiang Low

Published: 21 Apr 2025, Last Modified: 21 Apr 2025AI4X 2025 OralEveryoneRevisionsBibTeXCC BY 4.0

Keywords: Physics-Informed Neural Network, PINNs, Experimental Design, AI For Physics

Confirmation Of Submission Requirements: I submit a previously published paper. It was published in an archival peer–reviewed venue on or after September 8th 2024, I specify the DOI in the field below, and I submit the camera-ready version of the paper.

DOI: https://iclr.cc/virtual/2025/poster/27871

Submission Number: 79

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