MSHL learns higher-order group relations from incomplete spatiotemporal observations via adaptive multi-scale hypergraph Laplacians and a safe neural refinement stage that improves imputation when structure is present.
Clustering with hypergraphs: the case for large hyperedges.IEEE transactions on pattern analysis and machine intelligence, 39(9):1697–1711, 2016
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Learning Higher-Order Structure from Incomplete Spatiotemporal Data: Multi-Scale Hypergraph Laplacians with Neural Refinement
MSHL learns higher-order group relations from incomplete spatiotemporal observations via adaptive multi-scale hypergraph Laplacians and a safe neural refinement stage that improves imputation when structure is present.