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Learning second order coupled differential equations that are subject to non-conservative forces
[article]
2021
arXiv
pre-print
In this article we address the question whether it is possible to learn the differential equations describing the physical properties of a dynamical system, subject to non-conservative forces, from observations of its realspace trajectory(ies) only. We introduce a network that incorporates a difference approximation for the second order derivative in terms of residual connections between convolutional blocks, whose shared weights represent the coefficients of a second order ordinary
arXiv:2010.11270v2
fatcat:iwfu7deyenagdjvrzafsl7tddu