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1

Janson, Svante, Tomasz Łuczak, and Andrzej Rucinski. Random Graphs. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2000. http://dx.doi.org/10.1002/9781118032718.

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2

Kolchin, V. F. Random graphs. Cambridge, UK: Cambridge University Press, 1999.

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3

International Seminar on Random Graphs and Probabilistic Methods in Combinatorics. (2nd 1985 Uniwersytet im. Adama Mickiewicza w Poznaniu. Instytut Matematyki). Random graphs '85. New York: North-Holland, 1987.

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4

Chatterjee, Sourav. Large Deviations for Random Graphs. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65816-2.

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5

Ceccherini-Silberstein, Tullio, Maura Salvatori, and Ecaterina Sava-Huss, eds. Groups, Graphs and Random Walks. Cambridge: Cambridge University Press, 2017. http://dx.doi.org/10.1017/9781316576571.

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6

Palka, Zbigniew. Asymptotic properties of random graphs. Warszawa: Państwowe Wydawn. Nauk., 1988.

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7

Grimmett, Geoffrey. Probability on graphs: Random processes on graphs and lattices. Cambridge: Cambridge University Press, 2010.

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8

Marchette, David J. Random Graphs for Statistical Pattern Recognition. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2004. http://dx.doi.org/10.1002/047172209x.

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9

Spencer, Joel. The Strange Logic of Random Graphs. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04538-1.

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10

Spencer, Joel H. The strange logic of random graphs. Berlin: Springer, 2001.

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11

Balińska, Krystyna Teresa. Algorithms for random graphs with bounded degree. Poznań: Wydawn. Politechniki Poznańskiej, 1996.

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12

Woess, Wolfgang. Random walks on infinite graphs and groups. Cambridge: Cambridge University Press, 2000.

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13

Mikov, Aleksandr. Generalized graphs and grammars. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1013698.

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The textbook deals with ordinary graphs and their generalizations-hypergraphs, hierarchical structures, geometric graphs, random and dynamic graphs. Graph grammars are considered in detail. Meets the requirements of the federal state educational standards of higher education of the latest generation. For master's students studying in the areas of the 02.00.00 group "Computer and Information Sciences", and can also be used in senior bachelor's courses and other areas in the field of computer science and computer engineering.
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14

O'Connell, Neil. Some large deviation results for sparse random graphs. Bristol [England]: Hewlett Packard, 1996.

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15

Evstigneev, V. A. Teorii͡a︡ grafov: Algoritmy obrabotki beskonturnykh grafov. Novosibirsk: "Nauka," Sibirskoe predprii͡a︡tie RAN, 1998.

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16

Blanchard, Philippe, and Dimitri Volchenkov. Random Walks and Diffusions on Graphs and Databases. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19592-1.

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17

Heydenreich, Markus, and Remco van der Hofstad. Progress in High-Dimensional Percolation and Random Graphs. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62473-0.

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18

Newman, Mark. Random graphs. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805090.003.0011.

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An introduction to the mathematics of the Poisson random graph, the simplest model of a random network. The chapter starts with a definition of the model, followed by derivations of basic properties like the mean degree, degree distribution, and clustering coefficient. This is followed with a detailed derivation of the large-scale structural properties of random graphs, including the position of the phase transition at which a giant component appears, the size of the giant component, the average size of the small components, and the expected diameter of the network. The chapter ends with a discussion of some of the shortcomings of the random graph model.
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19

(Editor), Alan Frieze, and Tomasz Łuczak (Editor), eds. Random Graphs: Volume 2 (Random Graphs). Wiley-Interscience, 1992.

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20

Kolchin, V. F. Random Graphs. Cambridge University Press, 2010.

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21

Bollobás, Béla. Random Graphs. Cambridge University Press, 2012.

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22

Random Graphs. Wiley-Interscience, 2000.

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23

Random graphs. 2nd ed. Cambridge: Cambridge University Press, 2001.

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24

Kolchin, V. F. Random Graphs. Cambridge University Press, 2009.

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25

Bollobás, Béla. Random Graphs. Cambridge University Press, 2011.

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26

Janson, Svante, Andrzej Rucinski, and Tomasz Luczak. Random Graphs. Wiley & Sons, Incorporated, John, 2011.

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27

Janson, Svante, Andrzej Rucinski, and Tomasz Luczak. Random Graphs. Wiley & Sons, Incorporated, John, 2011.

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28

Kolchin, V. F. Random Graphs. Cambridge University Press, 2011.

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29

Random graphs. London: Academic Press, 1985.

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30

Coolen, A. C. C., A. Annibale, and E. S. Roberts. Applications of random graphs. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0011.

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This chapter reviews graph generation techniques in the context of applications. The first case study is power grids, where proposed strategies to prevent blackouts have been tested on tailored random graphs. The second case study is in social networks. Applications of random graphs to social networks are extremely wide ranging – the particular aspect looked at here is modelling the spread of disease on a social network – and how a particular construction based on projecting from a bipartite graph successfully captures some of the clustering observed in real social networks. The third case study is on null models of food webs, discussing the specific constraints relevant to this application, and the topological features which may contribute to the stability of an ecosystem. The final case study is taken from molecular biology, discussing the importance of unbiased graph sampling when considering if motifs are over-represented in a protein–protein interaction network.
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31

Coolen, Ton, Alessia Annibale, and Ekaterina Roberts. Generating Random Networks and Graphs. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.001.0001.

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This book supports researchers who need to generate random networks, or who are interested in the theoretical study of random graphs. The coverage includes exponential random graphs (where the targeted probability of each network appearing in the ensemble is specified), growth algorithms (i.e. preferential attachment and the stub-joining configuration model), special constructions (e.g. geometric graphs and Watts Strogatz models) and graphs on structured spaces (e.g. multiplex networks). The presentation aims to be a complete starting point, including details of both theory and implementation, as well as discussions of the main strengths and weaknesses of each approach. It includes extensive references for readers wishing to go further. The material is carefully structured to be accessible to researchers from all disciplines while also containing rigorous mathematical analysis (largely based on the techniques of statistical mechanics) to support those wishing to further develop or implement the theory of random graph generation. This book is aimed at the graduate student or advanced undergraduate. It includes many worked examples, numerical simulations and exercises making it suitable for use in teaching. Explicit pseudocode algorithms are included to make the ideas easy to apply. Datasets are becoming increasingly large and network applications wider and more sophisticated. Testing hypotheses against properly specified control cases (null models) is at the heart of the ‘scientific method’. Knowledge on how to generate controlled and unbiased random graph ensembles is vital for anybody wishing to apply network science in their research.
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32

Karonski, Michal, and Jerzy Jaworski. Random Graphs '87. John Wiley & Sons, 1991.

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33

Random geometric graphs. Oxford: Oxford University Press, 2003.

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34

Karonski, M., and A. Rucinski. Random Graphs '83. Elsevier Science & Technology Books, 2011.

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35

Penrose, Mathew. Random Geometric Graphs. Oxford University Press, Incorporated, 2003.

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36

Karonski, M., and Z. Palka. Random Graphs '85. Elsevier Science & Technology Books, 2011.

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37

Random Graphs (Mathematics Studies). North-Holland Publishing Co, 1987.

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38

Michał Karoński and Alan Frieze. Introduction to Random Graphs. Cambridge University Press, 2015.

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39

Frieze, Alan, and Michał Karoński. Introduction to Random Graphs. Cambridge University Press, 2015.

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40

Frieze, Alan, and Michał Karoński. Introduction to Random Graphs. Cambridge University Press, 2015.

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41

Hatami, Hamed. Randomly coloring graphs and coloring random graphs. 2005.

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42

Durrett, Rick. Random Graph Dynamics. Cambridge University Press, 2006.

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43

Random Graph Dynamics. Cambridge University Press, 2010.

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44

Durrett, Rick. Random Graph Dynamics. Cambridge University Press, 2009.

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45

Durrett, Rick. Random Graph Dynamics. Cambridge University Press, 2007.

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46

Durrett, Rick. Random Graph Dynamics. Cambridge University Press, 2007.

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47

Coolen, Ton, Alessia Annibale, and Ekaterina Roberts. Generating Random Networks and Graphs. Oxford University Press, 2017.

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48

Zürich, Eidgenössische Technische Hochschule, ed. q-distributions and random graphs. 1994.

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49

Ceccherini-Silberstein, Tullio, Maura Salvatori, and Ecaterina Sava-Huss. Groups, Graphs and Random Walks. Cambridge University Press, 2017.

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50

Ceccherini-Silberstein, Tullio, Maura Salvatori, and Ecaterina Sava-Huss. Groups, Graphs and Random Walks. Cambridge University Press, 2017.

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