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New bounds for Ollivier-Ricci Curvature in hypergraphs detailed

This paper introduces new theoretical bounds for Ollivier-Ricci Curvature (ORC) in higher-order networks, specifically focusing on hypergraphs. The research details how the Bauer-Jost-Liu curvature bound applies to hypergraph ORC and analyzes its accuracy based on local mass and geometry. The study also explores computational applications, including a threshold cascade that preserves exact transport decisions, and verifies the findings through extensive numerical experiments on public-data instances. AI

RANK_REASON The cluster contains a research paper detailing theoretical bounds and computational applications for Ollivier-Ricci Curvature in hypergraphs. [lever_c_demoted from research: ic=1 ai=0.7]

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New bounds for Ollivier-Ricci Curvature in hypergraphs detailed

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The cluster contains a research paper detailing theoretical bounds and computational applications for Ollivier-Ricci Curvature in hypergraphs. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Wonwoo Kang, Heehyun Park ·

    Transport-Free Lower Bounds for Ollivier--Ricci Curvature in Higher-Order Networks: Scope, Tightness, and Computational Applications

    arXiv:2405.13302v2 Announce Type: replace Abstract: We study how the Bauer--Jost--Liu curvature bound applies to hypergraph Ollivier--Ricci curvature (ORC) and how its accuracy depends on local mass and geometry. An explicit weighted-graph representation shows how the graph theor…