Zobrazeno 1 - 10
of 72
pro vyhledávání: '"BACKHAUSZ, ÁGNES"'
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 epidemic spread. As we use flexible two-layer random graphs as the underl
Externí odkaz:
http://arxiv.org/abs/2407.07118
This study, to the best of our knowledge for the first time, delves into the spatiotemporal dynamics of Bitcoin transactions, shedding light on the scaling laws governing its geographic usage. Leveraging a dataset of IP addresses and Bitcoin addresse
Externí odkaz:
http://arxiv.org/abs/2309.11884
Autor:
Backhausz, Ágnes, Székely, György J.
Our main goal is to examine the role of communities in epidemic spread in a random graph model. More precisely, we consider a random graph model which consists of overlapping complete graphs, representing households, workplaces, school classes, and w
Externí odkaz:
http://arxiv.org/abs/2308.12655
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 contacts outside the households by a random scale-free graph. We build a t
Externí odkaz:
http://arxiv.org/abs/2303.02195
Consider a uniformly sampled random $d$-regular graph on $n$ vertices. If $d$ is fixed and $n$ goes to $\infty$ then we can relate typical (large probability) properties of such random graph to a family of invariant random processes (called "typical"
Externí odkaz:
http://arxiv.org/abs/2102.02653
Autor:
Backhausz, Ágnes, Bognár, Edit
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 transmitted, but also the variability of susceptibility. Different people ha
Externí odkaz:
http://arxiv.org/abs/2002.06926
Autor:
Backhausz, Ágnes, Rozner, Bence
In this paper we introduce the perturbed version of the Barab\'asi-Albert random graph with multiple type edges and prove the existence of the (generalized) asymptotic degree distribution. Similarly to the non-perturbed case, the asymptotic degree di
Externí odkaz:
http://arxiv.org/abs/1905.11329
Autor:
Backhausz, Agnes, Szegedy, Balazs
We present a new approach to graph limit theory which unifies and generalizes the two most well developed directions, namely dense graph limits (even the more general $L^p$ limits) and Benjamini--Schramm limits (even in the stronger local-global sett
Externí odkaz:
http://arxiv.org/abs/1811.00626
Autor:
Backhausz, Ágnes, Rozner, Bence
We deal with a general preferential attachment graph model with multiple type edges. The types are chosen randomly, in a way that depends on the evolution of the graph. In the $N$-type case, we define the (generalized) degree of a given vertex as $\b
Externí odkaz:
http://arxiv.org/abs/1707.05064
This paper is concerned with certain invariant random processes (called factors of IID) on infinite trees. Given such a process, one can assign entropies to different finite subgraphs of the tree. There are linear inequalities between these entropies
Externí odkaz:
http://arxiv.org/abs/1706.04937