SphUnc decomposes uncertainty via hyperspherical von Mises-Fisher latents and performs causal identification through structural models on those latents.
Higher-order interactions shape collective dynamics differently in hypergraphs and simplicial complexes.Nature communications, 14(1):1605, 2023
2 Pith papers cite this work. Polarity classification is still indexing.
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HYVINT introduces an intensity-driven incidence mechanism and tractable variational estimator for hypergraph generation, with error bounds and empirical gains in fidelity, novelty, and diversity.
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SphUnc: Hyperspherical Uncertainty Decomposition and Causal Identification via Information Geometry
SphUnc decomposes uncertainty via hyperspherical von Mises-Fisher latents and performs causal identification through structural models on those latents.
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HYVINT: Intensity-Driven Hypergraph Generation with Variational Representations
HYVINT introduces an intensity-driven incidence mechanism and tractable variational estimator for hypergraph generation, with error bounds and empirical gains in fidelity, novelty, and diversity.