Variational Integrator Networks for Physically Structured Embeddings

21 Oct 2019Steindor SaemundssonAlexander TereninKatja HofmannMarc Peter Deisenroth

Learning workable representations of dynamical systems is becoming an increasingly important problem in a number of application areas. By leveraging recent work connecting deep neural networks to systems of differential equations, we propose \emph{variational integrator networks}, a class of neural network architectures designed to preserve the geometric structure of physical systems... (read more)

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