1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.SI2024
Parameter estimation of epidemic spread in two-layer random graphs by classical and machine learning methods
Ágnes Backhausz, Edit Bognár, Villő Csiszár +2
Our main goal in this paper is to quantitatively compare the performance of classical methods to XGBoost and convolutional neural networks in a parameter estimation problem for epi…
q-bio.PE2023
Estimating the parameters of epidemic spread on two-layer random graphs: a classical and a neural network approach
Ágnes Backhausz, Edit Bognár, Villő Csiszár +2
In this paper, we study the spread of a classical SIR process on a two-layer random network, where the first layer represents the households, while the second layer models the cont…
physics.soc-ph2020★ 1 cited
Virus spread and voter model on random graphs with multiple type nodes
Ágnes Backhausz, Edit Bognár
When modelling epidemics or spread of information on online social networks, it is crucial to include not just the density of the connections through which infections can be transm…