Recognition Models to Learn Dynamics from Partial Observations with Neural ODEs

Identifying dynamical systems from experimental data is a notably difficult task. Prior knowledge generally helps, but the extent of this knowledge varies with the application, and customized models are often needed. Neural ordinary differential equations can be written as a flexible framework for s...

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Hauptverfasser:	Buisson-Fenet, Mona, Morgenthaler, Valery, Trimpe, Sebastian, Di Meglio, Florent
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Computer Science - Systems and Control
Online-Zugang:	Volltext bestellen
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