TSI-GNN: Extending Graph Neural Networks to Handle Missing Data in Temporal Settings
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We present a novel approach for imputing missing data that incorporates temporal information into bipartite graphs through an extension of graph representation learning. Missing data is abundant in several domains, particularly when observations are made over ... ...
