Discrete harmonic morphisms ensure exact random-walk projection under network coarse-graining, and Laplacian renormalization often produces exact instances of them on real networks.
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MoRER builds an ER model repository via feature distribution clustering of tasks, achieving competitive results with limited labels versus active learning, transfer learning, and self-supervised methods on three multi-source datasets.
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Harmonic morphisms and dynamical invariants in network renormalization
Discrete harmonic morphisms ensure exact random-walk projection under network coarse-graining, and Laplacian renormalization often produces exact instances of them on real networks.
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Efficient Model Repository for Entity Resolution: Construction, Search, and Integration
MoRER builds an ER model repository via feature distribution clustering of tasks, achieving competitive results with limited labels versus active learning, transfer learning, and self-supervised methods on three multi-source datasets.