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pro vyhledávání: '"Baggio P."'
Firing rate models are dynamical systems widely used in applied and theoretical neuroscience to describe local cortical dynamics in neuronal populations. By providing a macroscopic perspective of neuronal activity, these models are essential for inve
Externí odkaz:
http://arxiv.org/abs/2411.07388
The Hopfield model provides a mathematically idealized yet insightful framework for understanding the mechanisms of memory storage and retrieval in the human brain. This model has inspired four decades of extensive research on learning and retrieval
Externí odkaz:
http://arxiv.org/abs/2411.05849
This paper investigates the existence of a separation principle between model identification and control design in the context of model predictive control. First, we elucidate that the separation principle holds asymptotically in the number of data i
Externí odkaz:
http://arxiv.org/abs/2409.16717
Autor:
Baggio, Giosue, Murphy, Elliot
In a recent paper, Mandelkern & Linzen (2024) - henceforth M&L - address the question of whether language models' (LMs) words refer. Their argument draws from the externalist tradition in philosophical semantics, which views reference as the capacity
Externí odkaz:
http://arxiv.org/abs/2406.00159
In this paper, we address the finite time synchronization of a network of dynamical systems with time-varying interactions modeled using temporal networks. We synchronize a few nodes initially using external control inputs. These nodes are termed as
Externí odkaz:
http://arxiv.org/abs/2403.09127
Publikováno v:
Atmospheric Research, 2023, 290, pp.106776
The present study contributes to an increased understanding of pyro-convection phenomena by using a fire-atmosphere coupled simulation, and investigates in detail the large-scale meteorological conditions affecting Portugal during the occurrence of m
Externí odkaz:
http://arxiv.org/abs/2310.16478
Autor:
Baggio, Roberta, Muzy, Jean-François
We consider the problem of short-term forecasting of surface wind speed probability distribution. Our approach consists in predicting the parameters of a given probability density function by training a neural network model whose loss function is the
Externí odkaz:
http://arxiv.org/abs/2310.12088
Autor:
Casti, Umberto, Baggio, Giacomo, Benozzo, Danilo, Zampieri, Sandro, Bertoldo, Alessandra, Chiuso, Alessandro
In this paper, we consider stable stochastic linear systems modeling whole-brain resting-state dynamics. We parametrize the state matrix of the system (effective connectivity) in terms of its steady-state covariance matrix (functional connectivity) a
Externí odkaz:
http://arxiv.org/abs/2310.07262
Autor:
Mattheus Torquato, Eliel Gomes da Silva Neto, Magno de Assis Verly Heringer, Elisa Maria Baggio-Saitovich, Emilson Ribeiro Viana, Ronaldo Sergio de Biasi
Publikováno v:
Journal of Materials Research and Technology, Vol 33, Iss , Pp 7380-7390 (2024)
Recently, cubic ferrites (CFs) have been widely explored in biomedical applications, especially those that display superparamagnetism behavior due to the desirable absence of a remanent field. In this study, we report the self-stabilization of the ma
Externí odkaz:
https://doaj.org/article/6ea6cc4e8cc14aa3b0e0f54ad95e9c7f
Autor:
Miles R. Bryan III, Xu Tian, Jui-Heng Tseng, Baggio A. Evangelista, Joey V. Ragusa, Audra F. Bryan, Winifred Trotman, David Irwin, Todd J. Cohen
Publikováno v:
Acta Neuropathologica Communications, Vol 12, Iss 1, Pp 1-18 (2024)
Abstract Tauopathies, including Alzheimer’s disease (AD), are a class of neurodegenerative diseases characterized by the presence of insoluble tau inclusions. Tau phosphorylation has traditionally been viewed as the dominant post-translational modi
Externí odkaz:
https://doaj.org/article/a224761b89a941c684570125212d6515