Masked graph autoencoder-based multi-agent dynamic relational inference model for trajectory prediction

Dynamic relational inference models uncover potential complex system interactions, enabling trajectory prediction and improving the interpretability of underlying system dynamics. However, the existing models cannot accurately infer the structural evolution trends and complete dynamic processes of t...

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Bibliographic Details

Published in:	Neurocomputing (Amsterdam) Vol. 634; p. 129922
Main Authors:	Zhao, Fuyuan, Cao, Xiangang, Zhao, Jiangbin, Duan, Yong, Yang, Xin, Zhang, Xinyuan
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 14.06.2025
Subjects:	Dynamic relational inference Graph attention network Masked graph autoencoder Multi-agent Trajectory prediction Multi-agent Masked graph autoencoder Trajectory prediction Dynamic relational inference Graph attention network
ISSN:	0925-2312
Online Access:	Get full text
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