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1

Simmonds, William Francis. Complete parameterized presentations and almost convex Cayley graphs. [s.l.]: typescript, 1991.

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2

Scheffler, Petra. Linear-time algorithms for NP-complete problems restricted to partial k-trees. Berlin: Akademie der Wissenschaften der DDR, Karl-Weierstrass-Institut für Mathematik, 1987.

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3

John, Wagner. The complete America. London: Titan, 2003.

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4

Michael, Lark, ed. The compleat Terminal city. Milwaukie, OR: Dark Horse Books, 2012.

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5

Publishing, Spark, ed. Complete curriculum. New York: Spark Publishing, 2006.

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6

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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7

Kalia, Rajat. Complete Course in Physics (Graphs). Independently Published, 2017.

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8

Complete Course in Physics ( Graphs ). Lulu Press, Inc., 2017.

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9

Complete Course in Physics ( Graphs ). Lulu Press, Inc., 2017.

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10

Complete Course in Physics ( Graphs ). Lulu Press, Inc., 2017.

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11

Complete Course in Physics ( Graphs ). Lulu Press, Inc., 2017.

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12

Dorogovtsev, Sergey N., and José F. F. Mendes. The Nature of Complex Networks. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780199695119.001.0001.

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Abstract The researchers studying complex networks will acquire from this advanced modern book a number of new issues and ideas, not yet touched upon in other reference volumes. The book considers a wide range of networks and processes taking place on them, paying particular attention to the recently developed directions, methods, and techniques. It proposes a statistical mechanics view of random networks based on the concept of statistical ensembles, but approaches and methods of modern graph theory, concerning random graphs, overlap strongly with statistical physics. Hence mathematicians have a good chance to discover interesting things in this book, even though it does not contain mathematical proofs and trades off rigour for comprehension, brevity, and relevance. The book combines features of an advanced textbook, a reference book and a detailed review of the current state of the art. This book will be useful for undergraduate, master, and PhD students and young researchers from physics, multidisciplinary studies, computer science, and applied mathematics wishing to gain a serious insight into the principles of complex networks. The book can be used as a text in university courses on complex networks. It proposes to determined students not only a brief trip to the land of complex networks but an option to stay there forever.
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13

Mieghem, Piet van. Graph Spectra for Complex Networks. Cambridge University Press, 2010.

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14

Mieghem, Piet Van. Graph Spectra for Complex Networks. Cambridge University Press, 2012.

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15

Mieghem, Piet Van. Graph Spectra for Complex Networks. Cambridge University Press, 2011.

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16

Mieghem, Piet van. Graph Spectra for Complex Networks. Cambridge University Press, 2010.

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17

Graph spectra for complex networks. Cambridge: Cambridge University Press, 2011.

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18

Graph Spectra for Complex Networks. Cambridge University Press, 2023.

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19

Graph Spectra for Complex Networks. Cambridge University Press, 2023.

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20

Complete Portfolio of Graphs and Charts. Caddylak Systems, 1985.

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21

Hofstad, Remco van der. Random Graphs and Complex Networks: Volume 1. Cambridge University Press, 2016.

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22

Complete Course in Physics (Graphs) - First Edition. Lulu Press, Inc., 2018.

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23

Complete Course in Physics ( Graphs ) - 2nd Edition. Lulu Press, Inc., 2017.

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24

Complete Course in Physics (Graphs) - 2nd Edition. Lulu Press, Inc., 2018.

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25

Hofstad, Remco van der. Random Graphs and Complex Networks: Volume 1. Cambridge University Press, 2016.

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26

Kalia, Rajat, Manas Kalia, and Samantha Fox. Complete Course in Physics ( Graphs ) - 4th Edition. Independently Published, 2017.

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27

Kalia, Rajat, and Manas Kalia. Complete Course in Physics (Graphs) - 3rd Edition. Independently Published, 2017.

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28

Kalia, Rajat. Complete Course in Physics (Graphs) - 4th Edition. Independently Published, 2017.

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29

Kalia, Rajat, Manas Kalia, and Madhu Johal. Complete Course in Physics (Graphs) - First Edition. Independently Published, 2012.

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30

Kalia, Rajat. Complete Course in Physics (Graphs) - 2nd Edition. Independently Published, 2017.

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31

Kalia, Rajat, Manas Kalia, and Krishna Kumawat. Complete Course in Physics (Graphs) - 2nd Edition. Independently Published, 2016.

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32

Hofstad, Remco van der. Random Graphs and Complex Networks: Volume 1. Cambridge University Press, 2017.

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33

Kalia, Rajat. Complete Course in Physics ( Graphs) - 3rd Edition. Independently Published, 2017.

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34

Complete Course in Physics (Graphs) - First Edition. Lulu Press, Inc., 2018.

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35

Complete Course in Physics ( Graphs ) - 3rd Edition. Lulu Press, Inc., 2017.

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36

Complete Course in Physics (Graphs) - 4rd Edition. Lulu Press, Inc., 2018.

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37

Complete Course in Physics (Graphs) - 3rd Edition. Lulu Press, Inc., 2018.

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38

Practitioner's Guide to Graph Data: Applying Graph Thinking and Graph Technologies to Solve Complex Problems. O'Reilly Media, Incorporated, 2020.

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39

Graph theory and complex networks: An introduction. [S.l.]: Maarten van Steen, 2010.

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40

Complete Course in Physics (Graphs) - Extended First Edition. Lulu Press, Inc., 2018.

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41

Kalia, Rajat. Complete Course in Physics ( Graphs ) - Extended First Edition. Independently Published, 2017.

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42

Kalia, Rajat, Manas Kalia, and Pooja Duggal. Complete Course in Physics (Graphs) - Extended First Edition. Independently Published, 2017.

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43

Kalia, Rajat, Manas Kalia, and Malkit Singh. Complete Course in Physics ( Graphs ) - Extended 3rd Edition. Independently Published, 2017.

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44

Complete Course in Physics ( Graphs ) - Extended 3rd Edition. Lulu Press, Inc., 2017.

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45

Complete Course in Physics ( Graphs ) - Extended First Edition. Lulu Press, Inc., 2017.

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46

Vernizzi, Graziano, and Henri Orland. Complex networks. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.43.

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This article deals with complex networks, and in particular small world and scale free networks. Various networks exhibit the small world phenomenon, including social networks and gene expression networks. The local ordering property of small world networks is typically associated with regular networks such as a 2D square lattice. The small world phenomenon can be observed in most scale free networks, but few small world networks are scale free. The article first provides a brief background on small world networks and two models of scale free graphs before describing the replica method and how it can be applied to calculate the spectral densities of the adjacency matrix and Laplacian matrix of a scale free network. It then shows how the effective medium approximation can be used to treat networks with finite mean degree and concludes with a discussion of the local properties of random matrices associated with complex networks.
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47

The Complete Guide To Gracie Jiujitsu. Invisible Cities Press, 2008.

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48

Damarke, Velerion. Graph Paper Math - a Complete K-5 Resource. Lulu Press, Inc., 2014.

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49

Complete Solutions Manual to accompany (Precalculus: Functions and Graphs). PWS - Kent, 1987.

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50

Gilbert, Michael T. Complete Wraith. Clover Press, 2020.

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