A Weighted Statistical Network Modeling Approach to Product Competition Analysis by Yaxin Cui, Faez Ahmed, Zhenghui Sha, Lijun Wang, Yan Fu, Noshir Contractor, Wei Chen

“…Then, we propose a weighted network modeling approach by extending the valued exponential random graph model to investigate the effects of product features and network structures on product competition relations. …”
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Design of low-carbon planning model for vehicle path based on adaptive multi-strategy ant colony optimization algorithm by Qi Guo, Rui Li, Changjiang Zheng, Gwanggil Jeon

“…Experimental results demonstrate that ACGNN yields significant path planning outcomes on both public and custom-built datasets, surpassing the traditional Dijkstra’s shortest path algorithm, random graph network (RGN), and conventional GNN methodologies. …”
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Zero-One Law for Connectivity in Superposition of Random Key Graphs on Random Geometric Graphs by Y. Tang, Q. L. Li

“…For this class of random graphs, we establish a new version of a conjectured zero-one law for graph connectivity as the number of nodes becomes unboundedly large. …”
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Spectral properties, localization transition and multifractal eigenvectors of the Laplacian on heterogeneous networks by Jeferson D. da Silva, Diego Tapias, Peter Sollich, Fernando L. Metz

“…In this case, the corresponding eigenvectors display localization properties reminiscent of the critical point of the Anderson localization transition on random graphs.…”
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Synthetic graphs for link prediction benchmarking by Alexey Vlaskin, Eduardo G Altmann

“…We propose a family of random graphs that incorporates both micro-scale motifs and meso-scale communities, two ubiquitous structures in complex networks. …”
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Spreading Social Influence with both Positive and Negative Opinions in Online Networks by Jing (Selena) He, Meng Han, Shouling Ji, Tianyu Du, Zhao Li

“…Finally, to validate the proposed greedy algorithm, we conduct extensive simulations and experiments on random graphs and seven different real-world data sets that represent small-, medium-, and large-scale networks.…”
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Approximate Solutions of Combinatorial Problems via Quantum Relaxations by Bryce Fuller, Charles Hadfield, Jennifer R. Glick, Takashi Imamichi, Toshinari Itoko, J. Richard Thompson, Yang Jiao, M. Marna Kagele, W. Blom-Schieber Adriana, Rudy Raymond, Antonio Mezzacapo

“…The proposed quantum relaxations inherit memory compression from quantum random access codes, which allowed us to test the performances of the methods presented for 3-regular random graphs and a design problem motivated by industry for sizes up to 40 nodes, on superconducting quantum processors.…”
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