Discussing the spectrum of physics-enhanced machine learning: a survey on structural mechanics applications

The intersection of physics and machine learning has given rise to the physics-enhanced machine learning (PEML) paradigm, aiming to improve the capabilities and reduce the individual shortcomings of data- or physics-only methods. In this paper, the spectrum of PEML methods, expressed across the defi...

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Bibliographic Details
Main Authors: Marcus Haywood-Alexander, Wei Liu, Kiran Bacsa, Zhilu Lai, Eleni Chatzi
Format: Article
Language:English
Published: Cambridge University Press 2024-01-01
Series:Data-Centric Engineering
Subjects:
Online Access:https://www.cambridge.org/core/product/identifier/S2632673624000339/type/journal_article