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of 1 284
pro vyhledávání: '"P. Marullo"'
Hebbian learning theory is rooted in Pavlov's Classical Conditioning. In addition, while mathematical models of the former have been proposed and studied in the past decades, especially in spin glass theory, only recently it has been numerically show
Externí odkaz:
http://arxiv.org/abs/2405.03823
Autor:
Betti, Alessandro, Casoni, Michele, Gori, Marco, Marullo, Simone, Melacci, Stefano, Tiezzi, Matteo
Optimal control deals with optimization problems in which variables steer a dynamical system, and its outcome contributes to the objective function. Two classical approaches to solving these problems are Dynamic Programming and the Pontryagin Maximum
Externí odkaz:
http://arxiv.org/abs/2312.09310
Autor:
Michael N. Maxwell, Anthony L. Marullo, Esther Valverde‐Pérez, Aoife D. Slyne, Ben T. Murphy, Ken D. O'Halloran
Publikováno v:
Experimental Physiology, Vol 109, Iss 8, Pp 1370-1384 (2024)
Abstract Duchenne muscular dystrophy (DMD) is characterised by respiratory muscle injury, inflammation, fibrosis and weakness, ultimately culminating in respiratory failure. The dystrophin‐deficient mouse model of DMD (mdx) shows evidence of respir
Externí odkaz:
https://doaj.org/article/09f19efea05444af83082d168ee8fe1a
The intrinsic difficulty in adapting deep learning models to non-stationary environments limits the applicability of neural networks to real-world tasks. This issue is critical in practical supervised learning settings, such as the ones in which a pr
Externí odkaz:
http://arxiv.org/abs/2306.02947
Publikováno v:
Entropy 2023, 25(2), 216
The aim of the present paper is to provide a preliminary investigation of the thermodynamics of particles obeying monotone statistics. To render the potential physical applications realistic, we propose a modified scheme called block-monotone, based
Externí odkaz:
http://arxiv.org/abs/2301.11016
Autor:
Meloni, Enrico, Faggi, Lapo, Marullo, Simone, Betti, Alessandro, Tiezzi, Matteo, Gori, Marco, Melacci, Stefano
In this paper, we present PARTIME, a software library written in Python and based on PyTorch, designed specifically to speed up neural networks whenever data is continuously streamed over time, for both learning and inference. Existing libraries are
Externí odkaz:
http://arxiv.org/abs/2210.09147
Autor:
Giorgia Marullo, Luca Ulrich, Francesca Giada Antonaci, Andrea Audisio, Alessandro Aprato, Alessandro Massè, Enrico Vezzetti
Publikováno v:
Bone Reports, Vol 22, Iss , Pp 101801- (2024)
Femur fractures are a significant worldwide public health concern that affects patients as well as their families because of their high frequency, morbidity, and mortality. When employing computer-aided diagnostic (CAD) technologies, promising result
Externí odkaz:
https://doaj.org/article/b29e715b83f24108849b9e8ed7cb05a5
As well known, Hebb's learning traces its origin in Pavlov's Classical Conditioning, however, while the former has been extensively modelled in the past decades (e.g., by Hopfield model and countless variations on theme), as for the latter modelling
Externí odkaz:
http://arxiv.org/abs/2207.00790
Autor:
Tiezzi, Matteo, Marullo, Simone, Faggi, Lapo, Meloni, Enrico, Betti, Alessandro, Melacci, Stefano
Devising intelligent agents able to live in an environment and learn by observing the surroundings is a longstanding goal of Artificial Intelligence. From a bare Machine Learning perspective, challenges arise when the agent is prevented from leveragi
Externí odkaz:
http://arxiv.org/abs/2204.12193
Autor:
P. MARULLO REEDTZ
Publikováno v:
Moneta e Credito, Vol 34, Iss 136 (2013)
A brief response to Niccoli’s The effect of growth limits on the loan/deposit ratio. JEL: E51, E52, G21
Externí odkaz:
https://doaj.org/article/70200e90266743cbb7ef2cd3ff3f300c