Embedding and Trajectories of Temporal Networks

Temporal network data are increasingly available in various domains, and often represent highly complex systems with intricate structural and temporal evolutions. Due to the difficulty of processing such complex data, it may be useful to coarse grain temporal network data into a numeric trajectory e...

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Bibliographic Details
Main Authors: Chanon Thongprayoon, Lorenzo Livi, Naoki Masuda
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10103875/

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