Book review: Random graphs, by V. F. Kolchin by W. Klonowski

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Structify-Net: Random Graph generation with controlled size and customized structure by Cazabet, Remy, Citraro, Salvatore, Rossetti, Giulio

Subjects: “…Network Generation, Random Graphs, Network Structure, Python Library…”
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Stochastic step-wise feature selection for Exponential Random Graph Models (ERGMs). by Helal El-Zaatari, Fei Yu, Michael R Kosorok

“…This study introduces a novel methodology for endogenous variable selection in Exponential Random Graph Models (ERGMs) to enhance the analysis of social networks across various scientific disciplines. …”
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ergm 4: New Features for Analyzing Exponential-Family Random Graph Models by Pavel N. Krivitsky, David R. Hunter, Martina Morris, Chad Klumb

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Exploring Coinvestment Partner Selection Strategies Using Exponential Random Graph Models by Jie Ren

“…This research analyzes cooperative relationships using exponential random graph models, considering both structural effects and node attributes. …”
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Scale-Free Property for Degrees and Weights in a Preferential Attachment Random Graph Model by István Fazekas, Bettina Porvázsnyik

“…A random graph evolution mechanism is defined. The evolution studied is a combination of the preferential attachment model and the interaction of four vertices. …”
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Does network homophily persist in multicultural volunteering programs? Results from an Exponential Random Graph Model by Qiuchang (Katy) Cao, Holly Dabelko-Schoeny, Keith Warren, Mo Yee Lee

“…Russian, Khmer, Somali, Nepali, and English-speaking older volunteers in the SCP (N = 41) identified friends through a nomination form. Exponential Random Graph Modeling (ERGM) was used to identify statistically significant structural features of the SCP network. …”
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With just one tap. Network study of tweets dissemination during the war in Ukraine by Marcin Wozniak

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A continuous-time network evolution model describing $ N $-interactions by István Fazekas, Attila Barta, László Fórián, Bettina Porvázsnyik

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Structural phase transitions in neural networks by Tatyana S. Turova

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What can mathematical models tell us about the relationship between circular migrations and HIV transmission dynamics? by Aditya S. Khanna, Dobromir T. Dimitrov, Steven M. Goodreau

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Geometric preferential attachment with choice-based edge step by Yu.A. Malyshkin

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Vertex degree distributions of growing graphs: calculation methods using error control by V. N. Zadorozhnyi, E. B. Yudin, V. A. Badryzlov

Subjects: “…random graphs with nonlinear preferential attachment rule…”
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From Net Topology to Synchronization in HR Neuron Grids by Stefano Cosenza, Paolo Crucitti, Luigi Fortuna, Mattia Frasca, Manuela La Rosa, Cecilia Stagni, Lisa Usai

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The Spatial Pattern and Influencing Factors of the Intercity Real Estate Investment Network in the Yangtze River Delta by Dai Liang, Lyu Yifan, Zheng Huibin, Li Luqi

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Triadic balance and network evolution in predictive models of signed networks by Hsuan-Wei Lee, Pei-Chin Lu, Hsiang-Chuan Sha, Hsini Huang

“…We analyze the impact of these structures on temporal network evolution by incorporating them into exponential random graph models across five networks of varying size, density, and directionality. …”
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Erdős–Rényi Poissonized by Curien, Nicolas

“…We introduce a variant of the Erdős–Rényi random graph where the number of vertices is random and follows a Poisson law. …”
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On the birthday problem: some generalizations and applications by P. N. Rathie, P. Zörnig

“…The distribution is generalized in two possible directions, one of them consists in considering a random graph with a single attracting center. Possible applications are also indicated.…”
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Approach for distributed BPEL engine placement using K-means by Rong-heng LIN, Bu-dan WU, Yao ZHAO, Fang-chun YANG

“…How to apply the algorithm in dif-ferent network topologies was also discussed, such as random graph and tree network. In the end, statistical software R was used as experiment tool to evaluate the algorithm. …”
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Public key based key distribution scheme for wireless sensor networks by HUANG Jie1, HUANG Bei1

“…Since key pre-distribution schemes based on symmetric key can not completely solve security problems of keys distribution in WSN,a new public key based key distribution scheme was proposed.In the scheme,public key set was generated by an initial public key set and a hash function in base station.Each sensor device was pre-distributed one public/private pair-wise key from public key set and a public key subset from the initial public keys set.Owing to uniqueness of private key,not only the communication security problems could be improved for WSN.but also the sensor-memory cost could be decreased.With the theorem of random-graph theory,the connectivity and scalability were illustrated.The results showed that the scheme was superior to the traditional key pre-distribution schemes.…”
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