Beven, Keith (2026) Deep Learning, Epistemic Uncertainties and the Inexact Sciences. Hydrological Processes, 40 (3): e70489. ISSN 0885-6087
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Abstract
This commentary considers the recent explosion of models based on Deep Learning/Machine Learning methods in hydrological journals and how their application might better contribute to hydrological understanding in the face of epistemic uncertainties in an inexact science.
Item Type:
Journal Article
Journal or Publication Title:
Hydrological Processes
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2300/2312
Subjects:
?? machine learningdisinformationepistemic uncertaintywater science and technology ??
Departments:
ID Code:
236300
Deposited By:
Deposited On:
27 Mar 2026 13:50
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Apr 2026 23:09