Causal hybrid modeling with double machine learning—applications in carbon flux modeling

Hybrid modeling integrates machine learning with scientific knowledge to enhance interpretability, generalization, and adherence to natural laws. Nevertheless, equifinality and regularization biases pose challenges in hybrid modeling to achieve these purposes. This paper introduces a novel approach...

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Bibliographic Details

Published in:	Machine Learning: Science and Technology
Main Authors:	Kai-Hendrik Cohrs, Gherardo Varando, Nuno Carvalhais, Markus Reichstein, Gustau Camps-Valls
Format:	Article
Language:	English
Published:	IOP Publishing 2024-01-01
Subjects:	knowledge-guided machine learning hybrid modeling causal effect estimation double machine learning temperature sensitivity carbon flux partitioning
Online Access:	https://doi.org/10.1088/2632-2153/ad5a60