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pro vyhledávání: '"Longo, Luca"'
Explainable Artificial Intelligence has gained significant attention due to the widespread use of complex deep learning models in high-stake domains such as medicine, finance, and autonomous cars. However, different explanations often present differe
Externí odkaz:
http://arxiv.org/abs/2404.10387
Autor:
Longo, Luca, Brcic, Mario, Cabitza, Federico, Choi, Jaesik, Confalonieri, Roberto, Del Ser, Javier, Guidotti, Riccardo, Hayashi, Yoichi, Herrera, Francisco, Holzinger, Andreas, Jiang, Richard, Khosravi, Hassan, Lecue, Freddy, Malgieri, Gianclaudio, Páez, Andrés, Samek, Wojciech, Schneider, Johannes, Speith, Timo, Stumpf, Simone
Publikováno v:
Information Fusion 2024
As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with prac
Externí odkaz:
http://arxiv.org/abs/2310.19775
Controllable timbre synthesis has been a subject of research for several decades, and deep neural networks have been the most successful in this area. Deep generative models such as Variational Autoencoders (VAEs) have the ability to generate a high-
Externí odkaz:
http://arxiv.org/abs/2307.10283
Autor:
Rizzo, Lucas, Longo, Luca
This paper presents a novel framework for structured argumentation, named extend argumentative decision graph ($xADG$). It is an extension of argumentative decision graphs built upon Dung's abstract argumentation graphs. The $xADG$ framework allows f
Externí odkaz:
http://arxiv.org/abs/2306.15500
In audio processing applications, the generation of expressive sounds based on high-level representations demonstrates a high demand. These representations can be used to manipulate the timbre and influence the synthesis of creative instrumental note
Externí odkaz:
http://arxiv.org/abs/2301.07665