Results 1 to 10 of about 39,180 (271)

Central limit theorems for SIR epidemics and percolation on configuration model random graphs [PDF]

open access: yesAnnals of Applied Probability, 2021
We consider a stochastic SIR (susceptible $\to$ infective $\to$ recovered) epidemic defined on a configuration model random graph, in which infective individuals can infect only their neighbours in the graph during an infectious period which has an arbitrary but specified distribution.
Frank Ball
exaly   +8 more sources

A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models. [PDF]

open access: yesPLoS ONE, 2015
We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random
David A Rolls   +4 more
doaj   +11 more sources

The asymptotic variance of the giant component of configuration model random graphs [PDF]

open access: yesAnnals of Applied Probability, 2017
For a supercritical configuration model random graph it is well known that, subject to mild conditions, there exists a unique giant component, whose size $R_n$ is $O (n)$, where $n$ is the total number of vertices in the random graph. Moreover, there exists $0 < \rho \leq 1$ such that $R_n/n \convp \rho$ as $\nr$.
Frank Ball
exaly   +7 more sources

On conditional configuration graphs with random distribution of vertex degrees

open access: yesTransactions of the Karelian Research Centre of the Russian Academy of Sciences, 2016
We consider a configuration graph with N vertices. The degrees of the vertices are drawn independently from a discrete power-law distribution with positive parameter τ . They are equal to the number of each vertex’s numbered semiedges.
Yury Pavlov
doaj   +3 more sources

On comparing configuration graphs robustness in a random environment

open access: yesTransactions of the Karelian Research Centre of the Russian Academy of Sciences, 2018
We consider configuration graphs with vertex degrees distributed independently according to the power law, with a truncated parameter τ normally distributed on the interval (a, b).
Marina Leri
doaj   +3 more sources

A case of limit behaviour of vertex degrees in conditional configuration graphs

open access: yesTransactions of the Karelian Research Centre of the Russian Academy of Sciences, 2017
We consider configuration graphs with N vertices. The degrees of the verticesare independent identically distributed random variables according to power-lawdistribution with positive parameter .
Yury Pavlov
doaj   +4 more sources

Configuring Random Graph Models with Fixed Degree Sequences [PDF]

open access: yesSIAM Review, 2018
To appear in SIAM Review, June 2018. Code available at github.com/joelnish/double-edge-swap-mcmc.
Daniel Larremore   +2 more
exaly   +4 more sources

Graph–Tabular Latent Fusion for Non-Contact Body Temperature Prediction from Thermal Facial Landmarks [PDF]

open access: yesSensors
Non-contact body-temperature prediction from facial thermography is affected by pose, occlusion, missing measurements, and inter-subject variation. This study proposes a graph–tabular latent-representation fusion framework for predicting body temperature
Yean Chun Ng   +5 more
doaj   +2 more sources

LIMIT BEHAVIOUR OF THE NUMBER OF EDGES IN A CONFIGURATION RANDOM GRAPH NEAR CRITICAL POINTS

open access: yesTransactions of the Karelian Research Centre of the Russian Academy of Sciences, 2015
We consider a configuration random graph with N vertices, whose degrees are independent and identically distributed according to power-law distribution with the parameter τ = τ(N). The properties of this graph depend on the value of the parameter τ. These
Yury Pavlov, Elena Feklistova
doaj   +3 more sources

Bridge Points Guided Neural Motion Planning in Complex Environments with Narrow Passages [PDF]

open access: yesSensors
Motion and path planning are fundamental to intelligent robotic systems, enabling navigation. The objective is to generate collision-free trajectories in obstacle-rich configuration spaces (C-spaces) while meeting performance constraints. In environments
Songyi Dian   +3 more
doaj   +2 more sources

Home - About - Disclaimer - Privacy