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Journal of Mathematical Imaging and Vision
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https://dx.doi.org/10.48550/ar...
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Hypergraph p-Laplacians and Scale Spaces

Hypergraph \(p\)-Laplacians and scale spaces
Authors: Fazeny, Ariane; Tenbrinck, Daniel; Lukin, Kseniaa; Burger, Martin;

Hypergraph p-Laplacians and Scale Spaces

Abstract

AbstractThe aim of this paper is to revisit the definition of differential operators on hypergraphs, which are a natural extension of graphs in systems based on interactions beyond pairs. In particular, we focus on the definition of Laplacian and p-Laplace operators for oriented and unoriented hypergraphs, their basic properties, variational structure, and their scale spaces. We illustrate that diffusion equations on hypergraphs are possible models for different applications such as information flow on social networks or image processing. Moreover, the spectral analysis and scale spaces induced by these operators provide a potential method to further analyze complex data and their multiscale structure. The quest for spectral analysis and suitable scale spaces on hypergraphs motivates in particular a definition of differential operators with trivial first eigenfunction and thus more interpretable second eigenfunctions. This property is not automatically satisfied in existing definitions of hypergraph p-Laplacians, and we hence provide a novel axiomatic approach that extends previous definitions and can be specialized to satisfy such (or other) desired properties.

Country
Germany
Keywords

diffusion models, Social and Information Networks (cs.SI), FOS: Computer and information sciences, information flow, PDEs on (hyper)graphs, segmentation, hypergraph spectral clustering, Computer Science - Social and Information Networks, PDEs on graphs and networks (ramified or polygonal spaces), Computing methodologies for image processing, Hypergraphs, image processing, Random walks on graphs, hypergraphs, 05C65, 35R02, 91D30, 94A08 (Primary) 34L05, 35J05, 47B02, 91C20 (Secondary), denoising, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), info:eu-repo/classification/ddc/510

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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