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Found 2 papers, 1 papers with code
INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging
It aims to infer knowledge for (the things at) unobserved locations using the data from (the things at) observed locations during a given time period of interest.
ConTIG: Continuous Representation Learning on Temporal Interaction Graphs
Representation learning on temporal interaction graphs (TIG) is to model complex networks with the dynamic evolution of interactions arising in a broad spectrum of problems.
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