Efficient confidence interval computation for physics-aware machine learning of diffusion-sorption models

The FInite Volume Neural Network (FINN) is an advanced, physics-aware machine learning (ML) framework that merges the structure and accuracy of traditional numerical methods with the flexibility of artificial neural networks. Its goal is to learn the unknown components (terms or parameters) of only...

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Bibliografische Detailangaben

Hauptverfasser:	Stefania Scheurer, Riccardo Frenner, Tim Brünnette, Sergey Oladyshkin, Wolfgang Nowak
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Frontiers Media S.A. 2026-05-01
Schriftenreihe:	Frontiers in Water
Schlagworte:	data-driven bootstrapping data-scarcity physics-aware machine learning subsurface hydrology uncertainty quantification
Online-Zugang:	https://www.frontiersin.org/articles/10.3389/frwa.2026.1813791/full
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