Zobrazeno 1 - 10
of 1 879
pro vyhledávání: '"Restrepo, Juan"'
In traditional models of opinion dynamics, each agent in a network has an opinion and changes in opinions arise from pairwise (i.e., dyadic) interactions between agents. However, in many situations, groups of individuals can possess a collective opin
Externí odkaz:
http://arxiv.org/abs/2408.13336
Autor:
Sampson, Corbit R., Restrepo, Juan G.
The spread of disinformation (maliciously spread false information) in online social networks has become an important problem in today's society. Disinformation's spread is facilitated by the fact that individuals often accept false information based
Externí odkaz:
http://arxiv.org/abs/2408.10373
Efficient and accurate prediction of physical systems is important even when the rules of those systems cannot be easily learned. Reservoir computing, a type of recurrent neural network with fixed nonlinear units, is one such prediction method and is
Externí odkaz:
http://arxiv.org/abs/2408.09223
We analyze the Bass model and the Susceptible-Infected (SI) model on hypergraphs with 3-body interactions. We derive the master equations for general hypernetworks, and use them to obtain explicit expressions for the expected adoption/infection level
Externí odkaz:
http://arxiv.org/abs/2407.12123
Motivated by the need to understand the factors driving gentrification, we introduce and analyze two simple dynamical systems that model the interplay between three potential drivers of the phenomenon. The constructed systems are based on the assumpt
Externí odkaz:
http://arxiv.org/abs/2406.12092
A Bayesian data assimilation scheme is formulated for advection-dominated advective and diffusive evolutionary problems, based upon the Dynamic Likelihood (DLF) approach to filtering. The DLF was developed specifically for hyperbolic problems -waves-
Externí odkaz:
http://arxiv.org/abs/2406.06837
In this paper we revisit the problem of decomposing a signal into a tendency and a residual. The tendency describes an executive summary of a signal that encapsulates its notable characteristics while disregarding seemingly random, less interesting a
Externí odkaz:
http://arxiv.org/abs/2401.04232
Reservoir computing is a machine learning framework where the readouts from a nonlinear system (the reservoir) are trained so that the output from the reservoir, when forced with an input signal, reproduces a desired output signal. A common implement
Externí odkaz:
http://arxiv.org/abs/2312.13151