Results 21 to 30 of about 56,162 (272)
Learning Causal Effects on Hypergraphs [PDF]
Knowledge Discovery and Data Mining, 2022 Hypergraphs provide an effective abstraction for modeling multi-way group interactions among nodes, where each hyperedge can connect any number of nodes.
Jing Ma +5 more
semanticscholar +1 more source
Contributions to Discrete Mathematics, 2018 This article emphasizes an extension of the study of metric and par- tition dimension to hypergraphs. We give a sharp lower bounds for the metric and partition dimension of hypergraphs in general and give exact values under specified conditions.eral and ...
Haider, Azeem +3 more
core +3 more sources
Node and edge nonlinear eigenvector centrality for hypergraphs [PDF]
Communications Physics, 2021 Network scientists have shown that there is great value in studying pairwise interactions between components in a system. From a linear algebra point of view, this involves defining and evaluating functions of the associated adjacency matrix. Recent work
Francesco Tudisco, D. Higham
semanticscholar +1 more source
Performance and limitations of the QAOA at constant levels on large sparse hypergraphs and spin glass models [PDF]
IEEE Annual Symposium on Foundations of Computer Science, 2022 The Quantum Approximate Optimization Algorithm (QAOA) is a general purpose quantum algorithm designed for combinatorial optimization. We analyze its expected performance and prove concentration properties at any constant level (number of layers) on ...
J. Basso +3 more
semanticscholar +1 more source
Influential groups for seeding and sustaining nonlinear contagion in heterogeneous hypergraphs [PDF]
Communications Physics, 2021 Contagion phenomena are often the results of multibody interactions—such as superspreading events or social reinforcement—describable as hypergraphs.
G. St‐Onge +6 more
semanticscholar +1 more source
Vital node identification in hypergraphs via gravity model [PDF]
Chaos, 2022 Hypergraphs that can depict interactions beyond pairwise edges have emerged as an appropriate representation for modeling polyadic relations in complex systems.
Xiaohui Xie +3 more
semanticscholar +1 more source
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2023 Complexity science provides a powerful framework for understanding physical, biological and social systems, and network analysis is one of its principal tools. Since many complex systems exhibit multilateral interactions that change over time, in recent years, network scientists have become increasingly interested in modelling and ...
Corinna Coupette +2 more
openaire +3 more sources
Journal of Combinatorial Theory, Series B, 2021 The following very natural problem was raised by Chung and Erd s in the early 80's and has since been repeated a number of times. What is the minimum of the Tur n number $\text{ex}(n,\mathcal{H})$ among all $r$-graphs $\mathcal{H}$ with a fixed number of edges?
Matija Bucić +3 more
openaire +4 more sources
Higher-order percolation processes on multiplex hypergraphs [PDF]
Physical Review E, 2021 Higher-order interactions are increasingly recognized as a fundamental aspect of complex systems ranging from the brain to social contact networks. Hypergraphs as well as simplicial complexes capture the higher-order interactions of complex systems and ...
Hanlin Sun, G. Bianconi
semanticscholar +1 more source
Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification [PDF]
Computer Vision and Pattern Recognition, 2020 Video-based person re-identification (re-ID) is an important research topic in computer vision. The key to tackling the challenging task is to exploit both spatial and temporal clues in video sequences.
Yichao Yan +6 more
semanticscholar +1 more source