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pro vyhledávání: '"Nenzi P"'
Integrating symbolic knowledge and data-driven learning algorithms is a longstanding challenge in Artificial Intelligence. Despite the recognized importance of this task, a notable gap exists due to the discreteness of symbolic representations and th
Externí odkaz:
http://arxiv.org/abs/2405.14389
Deep learning methods for time series have already reached excellent performances in both prediction and classification tasks, including anomaly detection. However, the complexity inherent in Cyber Physical Systems (CPS) creates a challenge when it c
Externí odkaz:
http://arxiv.org/abs/2405.10608
Autor:
Croia Michele, Burgio Nunzio, Ampollini Alessandro, Astorino Maria Denise, Bazzano Giulia, Bianchi Barbara, Cesaroni Mateo, Falconi Luca, Fiore Salvatore, Lepore Luigi, Nascetti Augusto, Nenzi Paolo, Pietropaolo Antonino, Ronsivalle Concetta, Santagata Alfonso, Ratto Antonino, Ricci Pierpaolo, Scaramuzzo Luigi
Publikováno v:
EPJ Web of Conferences, Vol 288, p 04009 (2023)
A collaboration between different facilities in Casaccia and Frascati ENEA research centers has recently opened the possibility of performing irradiation experiments using different kinds of particles such as protons, neutrons, and electrons. The fac
Externí odkaz:
https://doaj.org/article/65153a179522457aac1bb5a6c3334c31
Autor:
Uhrmacher, Adelinde, Frazier, Peter, Hähnle, Reiner, Klügl, Franziska, Lorig, Fabian, Ludäscher, Bertram, Nenzi, Laura, Ruiz-Martin, Cristina, Rumpe, Bernhard, Szabo, Claudia, Wainer, Gabriel A., Wilsdorf, Pia
Simulation has become, in many application areas, a sine-qua-non. Most recently, COVID-19 has underlined the importance of simulation studies and limitations in current practices and methods. We identify four goals of methodological work for addressi
Externí odkaz:
http://arxiv.org/abs/2310.05649
We introduce a similarity function on formulae of signal temporal logic (STL). It comes in the form of a kernel function, well known in machine learning as a conceptually and computationally efficient tool. The corresponding kernel trick allows us to
Externí odkaz:
http://arxiv.org/abs/2201.09928
We propose an interdisciplinary framework that combines Bayesian predictive inference, a well-established tool in Machine Learning, with Formal Methods rooted in the computer science community. Bayesian predictive inference allows for coherently inco
Externí odkaz:
http://arxiv.org/abs/2110.01360
From biological systems to cyber-physical systems, monitoring the behavior of such dynamical systems often requires to reason about complex spatio-temporal properties of physical and/or computational entities that are dynamically interconnected and a
Externí odkaz:
http://arxiv.org/abs/2109.08081
The Internet-of-Things, complex sensor networks, multi-agent cyber-physical systems are all examples of spatially distributed systems that continuously evolve in time. Such systems generate huge amounts of spatio-temporal data, and system designers a
Externí odkaz:
http://arxiv.org/abs/2106.08548
Publikováno v:
Logical Methods in Computer Science, Volume 18, Issue 1 (January 7, 2022) lmcs:7505
Cyber-Physical Systems (CPS) consist of inter-wined computational (cyber) and physical components interacting through sensors and/or actuators. Computational elements are networked at every scale and can communicate with each other and with humans. N
Externí odkaz:
http://arxiv.org/abs/2105.11400
Publikováno v:
In Nuclear Inst. and Methods in Physics Research, B February 2024 547