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Jun, 2023
理解和减轻物理启发神经网络中的外推失败
Understanding and Mitigating Extrapolation Failures in Physics-Informed Neural Networks
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Lukas Fesser, Richard Qiu, Luca D'Amico-Wong
TL;DR
该研究详细调查了基于PINNs的外推行为,并提供了证据,通过分析解函数的傅里叶谱,表征了产生有利外推行为的PDE,并展示了一种基于转移学习的策略,可将PINNs的外推误差降低高达82%。
Abstract
physics-informed neural networks
(
pinns
) have recently gained popularity in the scientific community due to their effective approximation of partial differential equations (
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