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Found 3 papers, 1 papers with code
SUSTeR: Sparse Unstructured Spatio Temporal Reconstruction on Traffic Prediction
In this paper, we tackle the problem of traffic prediction on sparse and spatially irregular and non-deterministic traffic observations.
Small Graph Is All You Need: DeepStateGNN for Scalable Traffic Forecasting
Unlike typical GNN methods that treat each traffic sensor as an individual graph node, DeepStateGNN clusters sensors into higher-level graph nodes, dubbed Deep State Nodes, based on various similarity criteria, resulting in a fixed number of nodes in a Deep State graph.
Discovering Motifs to Fingerprint Multi-Layer Networks: a Case Study on the Connectome of C. Elegans
Motif discovery is a powerful and insightful method to quantify network structures and explore their function.
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