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of 38
pro vyhledávání: '"Odor, Gergely"'
We study stationary epidemic processes in scale-free networks with local awareness behavior adopted by only susceptible, only infected, or all nodes. We find that while the epidemic size in the susceptible-aware and the all-aware scenarios scales lin
Externí odkaz:
http://arxiv.org/abs/2409.01384
The adoption of individual behavioural patterns is largely determined by stimuli arriving from peers via social interactions or from external sources. Based on these influences, individuals are commonly assumed to follow simple or complex adoption ru
Externí odkaz:
http://arxiv.org/abs/2406.18519
Autor:
Ódor, Gergely, Karsai, Márton
Behavior-disease models suggest that if individuals are aware and take preventive actions when the prevalence of the disease increases among their close contacts, then the pandemic can be contained in a cost-effective way. To measure the true impact
Externí odkaz:
http://arxiv.org/abs/2406.09983
We study SIR type epidemics on graphs in two scenarios: (i) when the initial infections start from a well connected central region, (ii) when initial infections are distributed uniformly. Previously, \'Odor et al. demonstrated on a few random graph m
Externí odkaz:
http://arxiv.org/abs/2304.11971
Inferring the source of a diffusion in a large network of agents is a difficult but feasible task, if a few agents act as sensors revealing the time at which they got hit by the diffusion. A main limitation of current source detection algorithms is t
Externí odkaz:
http://arxiv.org/abs/2112.14530
Publikováno v:
Proceedings of the National Academy of Sciences Oct 2021, 118 (41) e2112607118
It is a fundamental question in disease modelling how the initial seeding of an epidemic, spreading over a network, determines its final outcome. Research in this topic has primarily concentrated on finding the seed configuration which infects the mo
Externí odkaz:
http://arxiv.org/abs/2106.16070
The metric dimension (MD) of a graph is a combinatorial notion capturing the minimum number of landmark nodes needed to distinguish every pair of nodes in the graph based on graph distance. We study how much the MD can increase if we add a single edg
Externí odkaz:
http://arxiv.org/abs/2010.11023
Autor:
Komjáthy, Júlia, Ódor, Gergely
Publikováno v:
European Journal of Combinatorics 95 (2021) 103317
The metric dimension of a graph $G$ is the minimal size of a subset $R$ of vertices of $G$ that, upon reporting their graph distance from a distingished (source) vertex $v^\star$, enable unique identification of the source vertex $v^\star$ among all
Externí odkaz:
http://arxiv.org/abs/2002.08503
We study the problem of identifying the source of a stochastic diffusion process spreading on a graph based on the arrival times of the diffusion at a few queried nodes. In a graph $G=(V,E)$, an unknown source node $v^* \in V$ is drawn uniformly at r
Externí odkaz:
http://arxiv.org/abs/2002.07336
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