<p>Comparison of simulations using the CS algorithm with as cell-size threshold, with the pairwise algorithm for different outbreak stages. The y-axis indicate how many times faster (based on run time) the simulations using the CS algorithm were compared to the pairwise simulations.</p
<p>Comparison between predicted optimal grid size, , and best actual grid configuration apart from ....
<div><p>Numerical models for simulating outbreaks of infectious diseases are powerful tools for info...
The table lists the theoretical complexity and run-time (in seconds) of the four methods, SMASH, SPA...
<p>Average run time in seconds for each tested grid cell size up to and including the outbreak stage...
<p>Run time in seconds for simulations reaching 10, 100, 1000 and 10000 cumulative infected nodes. T...
<p>Comparison of transmission algorithms to the FSR method for simulations of outbreaks that were al...
The results are reported in terms of GED (the lower the better) as a function of the number of new n...
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
<p>Running times and prediction accuracies of the sub-quadratic algorithm tested with datasets of di...
<p>In A) different color lines represent the different likelihood-based algorithms tested for popula...
<p>The number of nodes is from 100 to 1000. Five random instances are generated based on each number...
<p>Italicized rows correspond to values of approximated from real cancer datasets. Each entry is me...
<p>The number of nodes is from 100 to 1000. Five random instances are generated based on each number...
Top row corresponds to the run-times in seconds of different methods in scenario (S1) and scenario (...
AbstractWe introduce the notion of expected hitting time to a goal as a measure of the convergence r...
<p>Comparison between predicted optimal grid size, , and best actual grid configuration apart from ....
<div><p>Numerical models for simulating outbreaks of infectious diseases are powerful tools for info...
The table lists the theoretical complexity and run-time (in seconds) of the four methods, SMASH, SPA...
<p>Average run time in seconds for each tested grid cell size up to and including the outbreak stage...
<p>Run time in seconds for simulations reaching 10, 100, 1000 and 10000 cumulative infected nodes. T...
<p>Comparison of transmission algorithms to the FSR method for simulations of outbreaks that were al...
The results are reported in terms of GED (the lower the better) as a function of the number of new n...
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
<p>Running times and prediction accuracies of the sub-quadratic algorithm tested with datasets of di...
<p>In A) different color lines represent the different likelihood-based algorithms tested for popula...
<p>The number of nodes is from 100 to 1000. Five random instances are generated based on each number...
<p>Italicized rows correspond to values of approximated from real cancer datasets. Each entry is me...
<p>The number of nodes is from 100 to 1000. Five random instances are generated based on each number...
Top row corresponds to the run-times in seconds of different methods in scenario (S1) and scenario (...
AbstractWe introduce the notion of expected hitting time to a goal as a measure of the convergence r...
<p>Comparison between predicted optimal grid size, , and best actual grid configuration apart from ....
<div><p>Numerical models for simulating outbreaks of infectious diseases are powerful tools for info...
The table lists the theoretical complexity and run-time (in seconds) of the four methods, SMASH, SPA...