SELFATTENTION GENERATIVE ADVERSARIAL NETWORKS


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AFfiLIATION NETWORKS - STANFORD UNIVERSITY

Kleinberg’s models, dubbed“small-world networks,” offer a nice starting point to analyze social networks3. A piece of folklore wisdom about social networks is the observation that friendship is mostly transitive, that is, if a and b are friends and b and c are friends, then there is a good chance that a and c are friends as well. Pub on Fri, 11 Sep 2020 16:38:00 GMT
Source: http://snap.stanford.edu/class/cs224w-readings/lattanzi09affiliation.pdf
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INTRODUCTION TO DYNAMIC NETWORKS

for dynamic networks •Challenge: –May not “know” the correct load on neighbors since links are going up and down •Key ideas: –Maintain an estimate of the neighbors’ load, and update it whenever the link is live –Be more conservative in sending tokens •Result: –Essentially same as for static networks, with a slightly Pub on Sun, 13 Sep 2020 10:52:00 GMT
Source: https://www.ccs.neu.edu/home/rraj/Talks/DynamicNetworks/DYNAMO/IntroDynamicNetworks.pdf
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CHAPTER 12 BARGAINING AND POWER IN NETWORKS

340 CHAPTER 12. BARGAINING AND POWER IN NETWORKS and the extent to which it is a property of network structure (i.e. someone is particularly powerful because they hold a pivotal position in the underlying social structure). Pub on Sat, 12 Sep 2020 20:33:00 GMT
Source: https://www.cs.cornell.edu/home/kleinber/networks-book/networks-book-ch12.pdf
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DISORDERED COMPLEX NETWORKS : ENERGY OPTIMAL LATTICES AND ...

networks, we compare their tails, that is, the probability that the SINR o ex-ceeds a certain level . This probability is known as the coverage probability (corresponding to the level ), and greater the coverage probability for a given , better is the network. Pub on Mon, 21 Sep 2020 01:24:00 GMT
Source: https://arxiv.org/pdf/2009.08811
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CHAPTER 21: NETWORKS IN FINANCE

Networks where insurance schemes are self-enforceable are either "thickly connected" or "thinly connected", whereas under intermediate degrees of connectedness, individuals are more likely to defect. In contrast, Bramoulle and Kranton (2007c) study the formation of risk-sharing networks. Pub on Sat, 12 Sep 2020 02:39:00 GMT
Source: http://finance.wharton.upenn.edu/~allenf/download/Vita/Allen%20and%20Babus%20-%20aug%2020-08-Long-SSRN.pdf
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INFERRING NETWORKS OF DIFFUSION AND INflUENCE

networks [Adar and Adamic 2005; Leskovec et al. 2006b, 2007c; Liben-Nowell and Kleinberg 2008]. In order to study paths of diffusion over networks, one essentially requires complete information about who influences whom, as a single missing link in a sequence of propagations can lead to wrong inferences [Sadikov et al. 2011]. Even Pub on Sun, 13 Sep 2020 09:19:00 GMT
Source: https://cs.stanford.edu/people/jure/pubs/netinf-tkdd12.pdf
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NETWORKS: PROPAGATION OF SHOCKS OVER ECONOMIC NETWORKS

Networks provide a natural framework for the study of how economic shocks are transmitted from one unit to another|from one industry, rm, bank, region, innovator,..., to another. Pub on Sun, 13 Sep 2020 21:01:00 GMT
Source: http://economics.mit.edu/files/9790
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ASIA AND GLOBAL PRODUCTION NETWORKS

networks: implications for trade, incomes and economic vulnerability Benno Ferrarini and David Hummels 1. INTRODUCTION Global value chains (GVCs) involve the production of goods and services through interlinked stages of production scattered across international borders. The international exchange of intermediate inputs, as opposed to Pub on Mon, 14 Sep 2020 21:50:00 GMT
Source: http://ssc.wisc.edu/~mchinn/asia-and-global-production-networks-sample.pdf
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INVESTIGATING NON-LINEARITIES WITH BAYESIAN NETWORKS

The results prove that Bayesian networks capture non -linear dependencies in real -world growth - oriented atmosphere data, as 57 percent of pairwise (unconditional) dependencies of the models are vaguely, and 29 percent severely, non -linear. The conclusion is that descriptive power of traditional linear models is at least in Pub on Tue, 22 Sep 2020 12:43:00 GMT
Source: https://pdfs.semanticscholar.org/245c/09463d946381fa01dbbcef26c97f62b2a354.pdf
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A STRATEGIC VISION FOR AMERICA S QUANTUM NETWORKS

A STRATEGIC VISION FOR AMERICA'S QUANTUM NETWORKS 2 INTRODUCTION The Trump Administration is committed to American leadership in quantum information science (QIS), Pub on Sun, 13 Sep 2020 08:08:00 GMT
Source: https://www.whitehouse.gov/wp-content/uploads/2017/12/A-Strategic-Vision-for-Americas-Quantum-Networks-Feb-2020.pdf
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