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pro vyhledávání: '"Brugnone, Nathan"'
The prevalence of graph-based data has spurred the rapid development of graph neural networks (GNNs) and related machine learning algorithms. Yet, despite the many datasets naturally modeled as directed graphs, including citation, website, and traffi
Externí odkaz:
http://arxiv.org/abs/2102.11391
Autor:
Brugnone, Nathan, Gonopolskiy, Alex, Moyle, Mark W., Kuchroo, Manik, van Dijk, David, Moon, Kevin R., Colon-Ramos, Daniel, Wolf, Guy, Hirn, Matthew J., Krishnaswamy, Smita
Publikováno v:
Proceedings of the 2019 IEEE International Conference on Big Data, pages 2624-2633, 2019
Big data often has emergent structure that exists at multiple levels of abstraction, which are useful for characterizing complex interactions and dynamics of the observations. Here, we consider multiple levels of abstraction via a multiresolution geo
Externí odkaz:
http://arxiv.org/abs/1907.04463
Autor:
Brugnone, Nathan, Benkler, Noam, Revay, Peter, Myhre, Rebecca, Friedman, Scott, Schmer-Galunder, Sonja, Gray, Steven, Gentile, James
Publikováno v:
Journal of Computational Social Science; 20240101, Issue: Preprints p1-51, 51p
Autor:
Knox, CB, Gray, Steven, Zareei, Mahdi, Wentworth, Chelsea, Aminpour, Payam, Wallace, Renee V, Hodbod, Jennifer, Brugnone, Nathan
Publikováno v:
Collective Intelligence; 10/20/2023, p1-23, 23p
Akademický článek
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Akademický článek
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Autor:
Zhang X; Michigan State University, Department of Computational Mathematics, Science & Engineering, East Lansing, Michigan, United States., He Y; University of Oxford, Department of Statistics, Oxford, England, United Kingdom., Brugnone N; Michigan State University, Department of Computational Mathematics, Science & Engineering, East Lansing, Michigan, United States.; Michigan State University, Department of Community Sustainability, East Lansing, Michigan, United States., Perlmutter M; University of California, Los Angeles, Department of Mathematics, Los Angeles, California, United States., Hirn M; Michigan State University, Department of Computational Mathematics, Science & Engineering, East Lansing, Michigan, United States.; Michigan State University, Department of Mathematics, East Lansing, Michigan, United States.; Michigan State University, Center for Quantum Computing, Science & Engineering, East Lansing, Michigan, United States.
Publikováno v:
Advances in neural information processing systems [Adv Neural Inf Process Syst] 2021 Dec; Vol. 34, pp. 27003-27015.