Zobrazeno 1 - 10
of 207
pro vyhledávání: '"MURPHY, CHARLES P."'
Predicting the evolution of a large system of units using its structure of interaction is a fundamental problem in complex system theory. And so is the problem of reconstructing the structure of interaction from temporal observations. Here, we find a
Externí odkaz:
http://arxiv.org/abs/2206.04000
Autor:
Hartle, Harrison, Klein, Brennan, McCabe, Stefan, Daniels, Alexander, St-Onge, Guillaume, Murphy, Charles, Hébert-Dufresne, Laurent
Publikováno v:
Proceedings of the Royal Society A (2020)
Quantifying the differences between networks is a challenging and ever-present problem in network science. In recent years a multitude of diverse, ad hoc solutions to this problem have been introduced. Here we propose that simple and well-understood
Externí odkaz:
http://arxiv.org/abs/2008.02415
Autor:
Laurence, Edward, Murphy, Charles, St-Onge, Guillaume, Roy-Pomerleau, Xavier, Thibeault, Vincent
Small disturbances can trigger functional breakdowns in complex systems. A challenging task is to infer the structural cause of a disturbance in a networked system, soon enough to prevent a catastrophe. We present a graph neural network approach, bor
Externí odkaz:
http://arxiv.org/abs/2006.05232
Publikováno v:
Nature Communications 12, 4720 (2021)
Forecasting the evolution of contagion dynamics is still an open problem to which mechanistic models only offer a partial answer. To remain mathematically or computationally tractable, these models must rely on simplifying assumptions, thereby limiti
Externí odkaz:
http://arxiv.org/abs/2006.05410
Autor:
Young, Jean-Gabriel, St-Onge, Guillaume, Laurence, Edward, Murphy, Charles, Hébert-Dufresne, Laurent, Desrosiers, Patrick
Publikováno v:
Phys. Rev. X 9, 041056 (2019)
Network growth processes can be understood as generative models of the structure and history of complex networks. This point of view naturally leads to the problem of network archaeology: reconstructing all the past states of a network from its struc
Externí odkaz:
http://arxiv.org/abs/1803.09191
Publikováno v:
Phys. Rev. E 97, 032309 (2018)
We present a general class of geometric network growth mechanisms by homogeneous attachment in which the links created at a given time $t$ are distributed homogeneously between a new node and the exising nodes selected uniformly. This is achieved by
Externí odkaz:
http://arxiv.org/abs/1710.01600
Publikováno v:
Phys. Rev. E 97, 022305 (2018)
We present a degree-based theoretical framework to study the susceptible-infected-susceptible (SIS) dynamics on time-varying (rewired) configuration model networks. Using this framework, we provide a detailed analysis of the stationary state that cov
Externí odkaz:
http://arxiv.org/abs/1709.09257
We investigate the susceptible-infected-susceptible dynamics on configuration model networks. In an effort for the unification of current approaches, we consider a network whose edges are constantly being rearranged, with a tunable rewiring rate $\om
Externí odkaz:
http://arxiv.org/abs/1701.01740
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Autor:
McKean, Heidi Ann, Nordstrom, James, Gaster, Sam, Whiting, Emily, Guardado, Jesse, Choudhry, Sabina, Johnson, Thomas, Casey, Matthew, Murphy, Charles, Grow, Joel, Sulaiman, Raed, Quist, Erin, O'Neill, Elizabeth, Stoltenberg, Kelci, Schultz, Jill
Publikováno v:
Journal of Clinical Oncology; 2024 Supplement 3, Vol. 42, p41-41, 235p
