Zobrazeno 1 - 10
of 437
pro vyhledávání: '"Giuseppe D'Alessio"'
Autor:
Kamila Zdybał, Giuseppe D’Alessio, Antonio Attili, Axel Coussement, James C. Sutherland, Alessandro Parente
Publikováno v:
Applications in Energy and Combustion Science, Vol 14, Iss , Pp 100131- (2023)
In many reacting flow systems, the thermo-chemical state-space is known or assumed to evolve close to a low-dimensional manifold (LDM). Various approaches are available to obtain those manifolds and subsequently express the original high-dimensional
Externí odkaz:
https://doaj.org/article/86a28e52d99c4a1e8856408dcbbaf323
Autor:
Varbella, Anna, Briens, Damien, Gjorgiev, Blazhe, D'Inverno, Giuseppe Alessio, Sansavini, Giovanni
The energy transition is driving the integration of large shares of intermittent power sources in the electric power grid. Therefore, addressing the AC optimal power flow (AC-OPF) effectively becomes increasingly essential. The AC-OPF, which is a fun
Externí odkaz:
http://arxiv.org/abs/2410.04818
Autor:
D'Inverno, Giuseppe Alessio, Moradizadeh, Saeid, Salavatidezfouli, Sajad, Africa, Pasquale Claudio, Rozza, Gianluigi
The complexity of the cardiovascular system needs to be accurately reproduced in order to promptly acknowledge health conditions; to this aim, advanced multifidelity and multiphysics numerical models are crucial. On one side, Full Order Models (FOMs)
Externí odkaz:
http://arxiv.org/abs/2410.03802
Publikováno v:
Data-Centric Engineering, Vol 3 (2022)
Externí odkaz:
https://doaj.org/article/d08ceefe8a9f4976ada8ac1dfbcc20dc
Autor:
Gianmarco Aversano, Giuseppe D’Alessio, Axel Coussement, Francesco Contino, Alessandro Parente
Publikováno v:
Results in Engineering, Vol 10, Iss , Pp 100223- (2021)
The combination of Proper Orthogonal Decomposition (POD) with Kriging has been shown to be a reliable choice for the development of Reduced-Order Models (ROMs) for the prediction of combustion data at unexplored operating conditions. In this study, P
Externí odkaz:
https://doaj.org/article/c6caf9e846394e11aac85bdb73210569
Publikováno v:
Data-Centric Engineering, Vol 2 (2021)
Externí odkaz:
https://doaj.org/article/6d996395dac441cabe53d51b8b0779c8
Any kind of network can be naturally represented by a Directed Acyclic Graph (DAG); additionally, activation functions can determine the reaction of each node of the network with respect to the signal(s) incoming. We study the characterization of the
Externí odkaz:
http://arxiv.org/abs/2402.06768
Reservoir Computing (RC) has become popular in recent years thanks to its fast and efficient computational capabilities. Standard RC has been shown to be equivalent in the asymptotic limit to Recurrent Kernels, which helps in analyzing its expressive
Externí odkaz:
http://arxiv.org/abs/2401.14557
Graph Neural Networks (GNNs) have emerged in recent years as a powerful tool to learn tasks across a wide range of graph domains in a data-driven fashion; based on a message passing mechanism, GNNs have gained increasing popularity due to their intui
Externí odkaz:
http://arxiv.org/abs/2401.12362
Autor:
Bucarelli, Maria Sofia, D'Inverno, Giuseppe Alessio, Bianchini, Monica, Scarselli, Franco, Silvestri, Fabrizio
In the context of deep learning models, attention has recently been paid to studying the surface of the loss function in order to better understand training with methods based on gradient descent. This search for an appropriate description, both anal
Externí odkaz:
http://arxiv.org/abs/2401.03824