Geological Literature Search (GEOLIS) (Geological Survey of Japan / AIST)

Hessian-based uncertainty quantification for Physics-Informed Neural Networks: Application to the frictional parameter estimation (STT38-P06)(poster session)(abs.)

Authors=Rikuto Fukushima, Masayuki Kano, Kazuro Hirahara, Makiko Ohtani

Journal/Book_names=Abstracts, Japan Geoscience Union Meeting (online)

volume=2024

pages=STT38-P06

Publish_year=2024

Publisher=Japan Geoscience Union

Language_of_Text=EN

ID=300044143

@id=https://gbank.gsj.jp/ld/resource/geolis/300044143