Zobrazeno 1 - 10
of 45 173
pro vyhledávání: '"D'HOLLANDER, A."'
Autor:
Flietner, Valentin, Heidergott, Bernd, Hollander, Frank den, Lindner, Ines, Parvaneh, Azadeh, Strulik, Holger
In this paper, we advance the network theory of aging and mortality by developing a causal mathematical model for the mortality rate. First, we show that in large networks, where health deficits accumulate at nodes representing health indicators, the
Externí odkaz:
http://arxiv.org/abs/2412.12815
Autor:
Hollander, F. den
The present paper is a brief overview of random opinion dynamics on random graphs based on the Ising Lecture given by the author at the World Congress in Probability and Statistics, 12--16 August 2024, Bochum, Germany. The content is a snapshot of an
Externí odkaz:
http://arxiv.org/abs/2410.17808
Autor:
Capannoli, F., Hollander, F. den
The present overview of interacting particle systems on random graphs collects the notes of a mini-course given by the authors at the Brazilian School of Probability, 5--9 August 2024, in Salvador, Bahia, Brazil. The content is a personal snapshot of
Externí odkaz:
http://arxiv.org/abs/2410.17766
We consider two-opinion voter models on dense dynamic random graphs. Our goal is to understand and describe the occurrence of consensus versus polarisation over long periods of time. The former means that all vertices have the same opinion, the latte
Externí odkaz:
http://arxiv.org/abs/2410.14618
Autor:
Zhang, Liang, Lin, Jionghao, Sabatini, John, Borchers, Conrad, Weitekamp, Daniel, Cao, Meng, Hollander, John, Hu, Xiangen, Graesser, Arthur C.
Learning performance data describe correct and incorrect answers or problem-solving attempts in adaptive learning, such as in intelligent tutoring systems (ITSs). Learning performance data tend to be highly sparse (80\%\(\sim\)90\% missing observatio
Externí odkaz:
http://arxiv.org/abs/2409.15631
Autor:
Sun, Xingzhi, Xu, Charles, Rocha, João F., Liu, Chen, Hollander-Bodie, Benjamin, Goldman, Laney, DiStasio, Marcello, Perlmutter, Michael, Krishnaswamy, Smita
In many data-driven applications, higher-order relationships among multiple objects are essential in capturing complex interactions. Hypergraphs, which generalize graphs by allowing edges to connect any number of nodes, provide a flexible and powerfu
Externí odkaz:
http://arxiv.org/abs/2409.09469
We consider a discrete-time binary branching random walk with independent standard normal increments subject to a penalty $\b$ for every pair of particles that get within distance $\e$ of each other at any time. We give a precise description of the m
Externí odkaz:
http://arxiv.org/abs/2407.15533
In this paper, we obtain a precise estimate of the probability that the sparse binomial random graph contains a large number of vertices in a triangle. The estimate of log of this probability is correct up to second order, and enables us to propose a
Externí odkaz:
http://arxiv.org/abs/2406.17390
Autor:
Baldassarri, Simone, Gaudillière, Alexandre, Hollander, Frank den, Nardi, Francesca Romana, Olivieri, Enzo, Scoppola, Elisabetta
This is the third in a series of three papers in which we study a lattice gas subject to Kawasaki dynamics at inverse temperature $\beta>0$ in a large finite box $\Lambda_\beta \subset \mathbb{Z}^2$ whose volume depends on $\beta$. Each pair of neigh
Externí odkaz:
http://arxiv.org/abs/2406.02099
Autor:
Ruis, Frank A., Liezenga, Alma M., Heslinga, Friso G., Ballan, Luca, Eker, Thijs A., Hollander, Richard J. M. den, van Leeuwen, Martin C., Dijk, Judith, Huizinga, Wyke
Collecting and annotating real-world data for the development of object detection models is a time-consuming and expensive process. In the military domain in particular, data collection can also be dangerous or infeasible. Training models on syntheti
Externí odkaz:
http://arxiv.org/abs/2405.19822