most citedInput-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.LG2022★ 2 cited

Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits

Alan Yang, Jie Xiong, Maxim Raginsky +1

This paper proposes a class of neural ordinary differential equations parametrized by provably input-to-state stable continuous-time recurrent neural networks. The model dynamics a…