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Neural Differential Algebraic Equations
March 20, 2024, 4:42 a.m. | James Koch, Madelyn Shapiro, Himanshu Sharma, Draguna Vrabie, Jan Drgona
cs.LG updates on arXiv.org arxiv.org
Abstract: Differential-Algebraic Equations (DAEs) describe the temporal evolution of systems that obey both differential and algebraic constraints. Of particular interest are systems that contain implicit relationships between their components, such as conservation relationships. Here, we present Neural Differential-Algebraic Equations (NDAEs) suitable for data-driven modeling of DAEs. This methodology is built upon the concept of the Universal Differential Equation; that is, a model constructed as a system of Neural Ordinary Differential Equations informed by theory from particular …
abstract arxiv components conservation constraints cs.lg data data-driven differential evolution methodology modeling relationships systems temporal type
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