Failure-averse Active Learning for Physics-constrained Systems
Failure-averse Active Learning for Physics-constrained Systems
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Ithaca: Cornell University Library, arXiv.org
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English
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Publisher
Ithaca: Cornell University Library, arXiv.org
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Contents
Active learning is a subfield of machine learning that is devised for design and modeling of systems with highly expensive sampling costs. Industrial and engineering systems are generally subject to physics constraints that may induce fatal failures when they are violated, while such constraints are frequently underestimated in active learning. In...
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Full title
Failure-averse Active Learning for Physics-constrained Systems
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TN_cdi_proquest_journals_2587496450
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2587496450
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E-ISSN
2331-8422
DOI
10.48550/arxiv.2110.14443
