Scholars deliver the first systematic survey of Dynamic GNNs, unifying continuous- and discrete-time models, benchmarking ...
Looks can be deceiving and that's one of the problems with today's three-dimensional bar graph. While these graphs may look correct, researchers from the Johns Hopkins Bloomberg School of ...
Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data
DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...
Graphs are widely used to represent complex relationships in everyday applications such as social networks, bioinformatics, and recommendation ...
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