A one-parameter 'return to previously visited nodes' model reveals strong memory in time-respecting paths across eight human-proximity datasets, and higher memory slows diffusion.
An embedding-based distance for temporal graphs
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Modeling memory in time-respecting paths on temporal networks
A one-parameter 'return to previously visited nodes' model reveals strong memory in time-respecting paths across eight human-proximity datasets, and higher memory slows diffusion.