Zobrazeno 1 - 10
of 1 728
pro vyhledávání: '"P Trezza"'
Autor:
Corrado Viola
Publikováno v:
Studi Veronesi, Vol 9, Iss 0, Pp 111-147 (2024)
After an initial investigation on the presence of Gaetano Trezza (1827-1892) in local and national public memory (city odonomastics, epigraphy, iconography, etc.), the essay retraces the life of the defrocked Veronese priest and apostle of positivism
Externí odkaz:
https://doaj.org/article/edbe298d4182410ca9eb16420d4afea0
Kniha
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Artificial Intelligence (AI) in materials science is driving significant advancements in the discovery of advanced materials for energy applications. The recent GNoME protocol identifies over 380,000 novel stable crystals. From this, we identify over
Externí odkaz:
http://arxiv.org/abs/2411.10125
We assume that a sufficiently large database is available, where a physical property of interest and a number of associated ruling primitive variables or observables are stored. We introduce and test two machine learning approaches to discover possib
Externí odkaz:
http://arxiv.org/abs/2401.05226
Autor:
Trezza, Giovanni, Chiavazzo, Eliodoro
It stands to reason that the amount and the quality of data is of key importance for setting up accurate AI-driven models. Among others, a fundamental aspect to consider is the bias introduced during sample selection in database generation. This is p
Externí odkaz:
http://arxiv.org/abs/2311.09891
Publikováno v:
IEEE Transactions on Vehicular Technology, 2023
The hybridization process has recently touched also the world of agricultural vehicles. Within this context, we develop an Energy Management Strategy (EMS) aiming at optimizing fuel consumption, while maintaining the battery state of charge. A typica
Externí odkaz:
http://arxiv.org/abs/2308.02203
Measurement-adaptive track initiation remains a critical design requirement of many practical multi-target tracking systems. For labeled random finite sets multi-object filters, prior work has been established to construct a labeled multi-object birt
Externí odkaz:
http://arxiv.org/abs/2307.06401
Gibbs sampling is one of the most popular Markov chain Monte Carlo algorithms because of its simplicity, scalability, and wide applicability within many fields of statistics, science, and engineering. In the labeled random finite sets literature, Gib
Externí odkaz:
http://arxiv.org/abs/2306.15135
Autor:
Trezza, Giovanni, Chiavazzo, Eliodoro
In this study, we evaluate several classifiers and focus on selecting a minimal set of appropriate material features. Our objective is to propose and discuss general strategies for reducing the number of descriptors required for material classificati
Externí odkaz:
http://arxiv.org/abs/2304.07592
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 3, Pp 1597-1618 (2024)
We assume that a sufficiently large database is available, where a physical property of interest and a number of associated ruling primitive variables or observables are stored. We introduce and test two machine learning approaches to discover possib
Externí odkaz:
https://doaj.org/article/d981eb6008bc4d589cb2f0a76dd849fa