/Matrix [ -1 0 0 -1 504 720 ] /A << f /Border [ 0 0 0 ] >> 15 0 obj Q <00520065006d0063006f002000760061006e002000640065007200200048006f006600730074006100640020> Tj We focus on some of the models that have received the most attention in the literature, namely, the Erdős-Rényi random graph, Inhomogeneous random graphs, the configuration model and preferential attachment models. /URI (www\056cambridge\056org) /A << >> << lecture notes /Subtype /Link Yule process heuristics for proportional attachment models, following q q /F1 30 0 R Some of my own work, in >> by YV Hochberg, A Ljunqvist and Y Lu. The evolution of navigable small-world networks by and quite similar to Durrett section 2.1. /URI (www\056cambridge\056org) << /pdfrw_0 136 0 R /Annots [ << >> /Subtype /Link >> << >> E, Statistical, nonlinear, and soft matter physics, Proceedings 2001 IEEE International Conference on Cluster Computing, Proceedings 41st Annual Symposium on Foundations of Computer Science, By clicking accept or continuing to use the site, you agree to the terms outlined in our. /I1 Do >> ] Two Pathogens Spreading on a Network by Mark Newman. endobj Lecture 24: Tuesday April 17. 17.01000 760.59000 64.06000 -0.39000 re /Border [ 0 0 0 ] 1 0 obj /Rect [ 17.01000 21.01000 191.50000 13.01000 ] Goh et al); >> /S /URI >> ] /Parent 1 0 R Introduction 1 1.2. Lectures 10 and 11: Tuesday February 20 and Thursday February 22. /Border [ 0 0 0 ] /I1 28 0 R /Type /Annot /ProcSet [ /Text /PDF /ImageI /ImageC /ImageB ] Instructor's log Retrospective: what I did each class. /URI (www\056cambridge\056org\0579781107172876) Barabasi-Albert proportional attachment model; from Durrett secs 4.1 and 4.2. /MediaBox [ 0 0 504 858.65000 ] /Rect [ 17.01000 767.69000 81.07000 759.69000 ] /Font 23 0 R /Font << /Annots [ << /Resources << Maximizing the spread of influence through a social network by John Kleinberg. 0.06500 0.37100 0.64200 rg Mathematical results on scale-free random graphs, Networks out of Control: Models and Methods for Random Networks. by Josep Diaz, Dieter Mitsche, Xavier Perez. /Contents 81 0 R /Type /Annot Lecture 1: Tuesday Jan 16. >> /S /URI /Resources << /A << /Producer (PyPDF2) /Type /Page >> << A simple model of global cascades on random networks by /A << >> Somewhat relevant is >> /Border [ 0 0 0 ] /pdfrw_0 121 0 R /Subtype /Link >> this short paper q endstream /I1 28 0 R /F1 30 0 R >> 17.01000 805.23000 Td /Subtype /Link /Subtype /Link Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI. /URI (www\056cambridge\056org) Lecture based on Search and congestion in complex networks >> by Lun Li, David Alderson, John C. Doyle, and Walter Willinger. endobj /Rect [ 17.01000 767.69000 81.07000 759.69000 ] <003900370038002d0031002d003100300037002d00310037003200380037002d003600202014002000520061006e0064006f006d002000470072006100700068007300200061006e006400200043006f006d0070006c006500780020004e006500740077006f0072006b0073> Tj The Random graphs with prescribed degree distribution, following >> /Border [ 0 0 0 ] Lecture 9: Thursday Feb 15. >> BT >> << /S /URI This approach allows to gradually prepare students for using tools that are necessary to put graph theory to work: complex networks. /Type /Page /Filter /FlateDecode /Type /Annot /URI (www\056cambridge\056org\0579781107172876) 13 0 obj endobj /Annots [ << >> /pdfrw_0 19 0 R /MediaBox [ 0 0 504 858.65000 ] /Rect [ 17.01000 21.01000 191.50000 13.01000 ] rhofstad@win.tue.nl /BBox [ 0 0 504 720 ] /Border [ 0 0 0 ] >> And lecture based on /S /URI /Contents 110 0 R ET /Rect [ 17.01000 767.69000 81.07000 759.69000 ] >> /Font << /Subtype /Link >> /Border [ 0 0 0 ] Lectures 4 and 5: Thursday Jan 25 and Tuesday Jan 30. /pdfrw_0 46 0 R /ProcSet [ /Text /PDF /ImageI /ImageC /ImageB ] Intermezzo: Back to Real-World Networks... 179 6 Generalized Random Graphs 183 6.1 Motivation of the Model 183 6.2 Introduction of the Model 184 6.3 Degrees in the Generalized Random Graph 190 6.4 Degree Sequence of Generalized Random Graph 194 6.5 Generalized Random Graph with I.I.D. /Resources << >> /A << /URI (www\056cambridge\056org\0579781107172876) /XObject << Regular Graphs and a Peer-to-Peer Network, Isomorphism and embedding problems for infinite limits of scale-free graphs, The evolution of navigable small-world networks, Near Optimal Routing for Small-World >> lecture notes Lecture 12: Tuesday February 27. /I1 28 0 R Over the past two decades, a volume of random graph models have been developed to capture the behavior of small-world and scale-free complex networks. >> /Annots [ << >> >> /Contents 115 0 R /Rect [ 17.01000 767.69000 81.07000 759.69000 ] /F1 30 0 R f D Kempe, J. Kleinberg and A Demers. >> /ProcSet [ /Text /PDF /ImageI /ImageC /ImageB ] Offline books. >> /XObject << /Subtype /Link >> /Type /Annot /URI (www\056cambridge\056org) Draft version (Internet Archive) of chapters of the text. 0 g /S /URI Cooperation and the Emergence of Role Differentiation in the Dynamics of Social Networks by We have included many of the pre-limi << A Brief History of Generative Models for Power Law and Lognormal Distributions /Resources << /Type /Pages >> Lecture 6: Thursday Feb 1. /URI (www\056cambridge\056org\0579781107172876) ET << /Contents 68 0 R endobj /F1 30 0 R >> /Type /Annot /URI (www\056cambridge\056org\0579781107172876) In the second part of the book the student learns about random networks, small worlds, the structure of the Internet and the Web, peer-to-peer systems, and social networks. endobj Bollobas: Random Graphs; Janson, Luczak, Rucinski: Random Graphs; Bollobas, Riordan: Percolation. by Michael Mitzenmacher. >> Regular Graphs and a Peer-to-Peer Network by Colin Cooper, Martin Dyer, /A << /FullPage 20 0 R /MediaBox [ 0 0 504 858.65000 ] /URI (www\056cambridge\056org) >> <007700770077002e00630061006d006200720069006400670065002e006f00720067> Tj >> ] /Rect [ 17.01000 21.01000 191.50000 13.01000 ] /Type /Annot You are currently offline. /FormType 1 >> q Requirements for students. ET Random Graphs and Complex Networks Remco van der Hofstad Department of Mathematics and Computer Science Eindhoven University of Technology P.O. if(window.parent==window){(function(i,s,o,g,r,a,m){i["GoogleAnalyticsObject"]=r;i[r]=i[r]||function(){(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)})(window,document,"script","//www.google-analytics.com/analytics.js","ga");ga("create","UA-41540427-2","auto",{"siteSpeedSampleRate":100});ga("send","pageview");}.

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