HiDeS: a higher-order-derivative-supervised neural ordinary differential equation for multi-robot systems and opinion dynamics

HiDeS: a higher-order-derivative-supervised neural ordinary differential equation for multi-robot systems and opinion dynamics

This paper addresses the limitations of current neural ordinary differential equations (NODEs) in modeling and predicting complex dynamics by introducing a novel framework called higher-order-derivative-supervised (HiDeS) NODE. This method extends traditional NODE frameworks by incorporating higher-...

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Bibliographic Details
Main Authors:	Meng Li, Wenyu Bian, Liangxiong Chen, Mei Liu
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2024-03-01
Series:	Frontiers in Neurorobotics
Subjects:	neural ordinary differential equations multi-robot systems opinion dynamics robotics neural networks
Online Access:	https://www.frontiersin.org/articles/10.3389/fnbot.2024.1382305/full

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