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HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs

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Published in:ArXiv cs.LG Recent Papers
Format: Online Article RSS Article
Published: 2026
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spellingShingle HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs
ArXiv cs.LG Recent Papers
Petroleum & Energy
Engineering & Technology
sub_discipline_display Petroleum & Energy
sub_discipline_facet Petroleum & Energy
subject_display ArXiv cs.LG Recent Papers
Petroleum & Energy
Engineering & Technology
ArXiv cs.LG Recent Papers
Petroleum & Energy
Engineering & Technology
subject_facet ArXiv cs.LG Recent Papers
Petroleum & Energy
Engineering & Technology
title HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs
title_auth HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs
title_full HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs
title_fullStr HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs
title_full_unstemmed HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs
title_short HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs
title_sort hycop: hybrid composition operators for interpretable learning of pdes
topic ArXiv cs.LG Recent Papers
Petroleum & Energy
Engineering & Technology
url https://arxiv.org/abs/2605.00820v1