Papers by Shohei Yamasaki

1 papers
Holistic Prediction on a Time-Evolving Attributed Graph (2023.acl-long)

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Challenge: Existing methods for predicting future links, nodes, and attributes of time-evolving attributed graphs are not accurate.
Approach: They propose a framework that predicts node attributes and topology changes such as appearance and disappearance of links and the emergence and loss of nodes.
Outcome: The proposed framework improves on existing methods that assume that each link, node, and attribute prediction is independent and fails to predict new nodes that were not observed in the past.

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