Embedding and trajectories of temporal networks

HIGHLIGHTS

  • who: CHANON THONGPRAYOON and colleagues from the Computational and Data-Enabled Science and Engineering Program, State University of New York at Buffalo, Buffalo, NY, USA have published the paper: Embedding and trajectories of temporal networks, in the Journal: (JOURNAL)
  • what: The authors propose a method to generate trajectories of temporal networks embedded in a low-dimensional space given a sequence of time-stamped events as input. The authors propose that this gap is because most methods for analyzing time series assume numeric data, whereas the temporal network data is network-valued by definition. In contrast . . .

     

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