Zobrazeno 1 - 10
of 6 156
pro vyhledávání: '"Stochastic block model"'
In this paper, we study the dynamics of the susceptible-infected-recovered (SIR) model on a network with community structure, namely the stochastic block model (SBM). As usual, the SIR model is a stochastic model for an epidemic where infected vertic
Externí odkaz:
http://arxiv.org/abs/2410.07097
This is the first of two complementary works in which we analyze the connected components of the degree-corrected stochastic block model (DCSBM). Our model is a random graph with an underlying community structure and degree in-homogeneity. It belongs
Externí odkaz:
http://arxiv.org/abs/2409.18894
We propose a functional stochastic block model whose vertices involve functional data information. This new model extends the classic stochastic block model with vector-valued nodal information, and finds applications in real-world networks whose nod
Externí odkaz:
http://arxiv.org/abs/2407.00564
Network data are observed in various applications where the individual entities of the system interact with or are connected to each other, and often these interactions are defined by their associated strength or importance. Clustering is a common ta
Externí odkaz:
http://arxiv.org/abs/2408.00651
Autor:
Mandal, Anirban, Chatterjee, Arindam
Sampling is frequently used to collect data from large networks. In this article we provide valid asymptotic prediction intervals for subgraph counts and clustering coefficient of a population network when a network sampling scheme is used to observe
Externí odkaz:
http://arxiv.org/abs/2407.19191
We study the disassortative stochastic block model with three communities, a well-studied model of graph partitioning and Bayesian inference for which detailed predictions based on the cavity method exist [Decelle et al. (2011)]. We provide strong ev
Externí odkaz:
http://arxiv.org/abs/2407.17851
We consider the problem of recovering the community structure in the stochastic block model. We aim to describe the mutual information between the observed network and the actual community structure as the number of nodes diverges while the average d
Externí odkaz:
http://arxiv.org/abs/2406.15233
We consider a recently proposed approach to graph signal processing based on graphons. We show how the graphon-based approach to GSP applies to graphs sampled from a stochastic block model. We obtain a basis for the graphon Fourier transform on such
Externí odkaz:
http://arxiv.org/abs/2406.06306
The stochastic block model (SBM) is a generalization of the Erd\H{o}s--R\'enyi model of random graphs that describes the interaction of a finite number of distinct communities. In sparse Erd\H{o}s--R\'enyi graphs, it is known that a linear-time algor
Externí odkaz:
http://arxiv.org/abs/2403.02140
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.