Outlier-resistant physics-informed neural network
Publication type: Journal Article
Publication date: 2025-02-20
scimago Q2
wos Q1
SJR: 0.705
CiteScore: 4.2
Impact factor: 2.4
ISSN: 24700045, 24700053, 15393755, 15502376, 1063651X, 10953787
Abstract
Recent advances in machine learning have introduced physics-informed neural networks (PINN) as a valuable tool for addressing dynamics through governing equations and experimental observations. Outliers can be present in measurements and significantly affect the accuracy of the solutions provided by PINN. To overcome this limitation, we construct an outlier-resistant PINN (OrPINN) based on Tsallis statistics. We investigate the robustness of OrPINN in describing the acoustic and linear elastic wave dynamics under various outlier-level scenarios. We find that the OrPINN can improve the accuracy of the solutions even when the data is highly corrupted.
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3
Total citations:
3
Citations from 2024:
3
(100%)
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Duarte D. H. G. et al. Outlier-resistant physics-informed neural network // Physical Review E. 2025. Vol. 111. No. 2. L023302
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Duarte D. H. G., Lima P. D. S. D., De Araujo J. M. Outlier-resistant physics-informed neural network // Physical Review E. 2025. Vol. 111. No. 2. L023302
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TY - JOUR
DO - 10.1103/physreve.111.l023302
UR - https://link.aps.org/doi/10.1103/PhysRevE.111.L023302
TI - Outlier-resistant physics-informed neural network
T2 - Physical Review E
AU - Duarte, D. H. G.
AU - Lima, Paulo Douglas Santos De
AU - De Araujo, Joao M
PY - 2025
DA - 2025/02/20
PB - American Physical Society (APS)
IS - 2
VL - 111
SN - 2470-0045
SN - 2470-0053
SN - 1539-3755
SN - 1550-2376
SN - 1063-651X
SN - 1095-3787
ER -
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@article{2025_Duarte,
author = {D. H. G. Duarte and Paulo Douglas Santos De Lima and Joao M De Araujo},
title = {Outlier-resistant physics-informed neural network},
journal = {Physical Review E},
year = {2025},
volume = {111},
publisher = {American Physical Society (APS)},
month = {feb},
url = {https://link.aps.org/doi/10.1103/PhysRevE.111.L023302},
number = {2},
pages = {L023302},
doi = {10.1103/physreve.111.l023302}
}