Inference of sequential patterns for neural message passing in temporal graphs

J von Pichowski, V Perri, L Qarkaxhija… - ar** network
T LaRock, M Xu, T Eliassi-Rad - EPJ Data Science, 2022 - epjds.epj.org
The maritime ship** network is the backbone of global trade. Data about the movement of
cargo through this network comes in various forms, from ship-level Automatic Identification …

Higher-order graph models: From theoretical foundations to machine learning (dagstuhl seminar 21352)

T Eliassi-Rad, V Latora, M Rosvall, I Scholtes - Dagstuhl Reports, 2021 - drops.dagstuhl.de
Graph and network models are essential for data science applications in computer science,
social sciences, and life sciences. They help to detect patterns in data on dyadic relations …

Zooming out on an evolving graph

A Aghasadeghi, VZ Moffitt, S Schelter… - Proceedings of the 23rd …, 2020 - par.nsf.gov
An evolving graph maintains the history of changes of graph topology and attribute values
over time. Such a graph has a specific temporal and structural resolution. It is often useful to …