Zobrazeno 1 - 10
of 2 641
pro vyhledávání: '"Venuto A"'
Pre-trained Vision-Language Models (VLMs) are able to understand visual concepts, describe and decompose complex tasks into sub-tasks, and provide feedback on task completion. In this paper, we aim to leverage these capabilities to support the traini
Externí odkaz:
http://arxiv.org/abs/2402.04764
Publikováno v:
Imagens da Educação, Vol 14, Iss 4 (2024)
O presente texto é fruto de uma pesquisa-ação que objetivou responder a seguinte questão: De que forma é possível desenvolver o conteúdo de lutas levando em consideração a realidade de disputas e conflitos entre os/as alunos/as de uma escola
Externí odkaz:
https://doaj.org/article/3a2202e83b464189ba7b5c4da7e1aea7
Autor:
Enrico Pompili, Giacomo Zaccherini, Salvatore Piano, Pierluigi Toniutto, Antonio Lombardo, Stefania Gioia, Giulia Iannone, Clara De Venuto, Marta Tonon, Roberta Gagliardi, Maurizio Baldassarre, Greta Tedesco, Giorgio Bedogni, Marco Domenicali, Vito Di Marco, Silvia Nardelli, Vincenza Calvaruso, Davide Bitetto, Paolo Angeli, Paolo Caraceni
Publikováno v:
JHEP Reports, Vol 6, Iss 12, Pp 101221- (2024)
Background & Aims: Long-term albumin (LTA) is currently standard of care for patients with decompensated cirrhosis in many Italian hepatology centres. In this real-life study, we aimed to describe patient, logistical and treatment-related characteris
Externí odkaz:
https://doaj.org/article/e57b81c6ec67447e8975b9cc0021ff4a
Publikováno v:
Clinical and Translational Science, Vol 17, Iss 11, Pp n/a-n/a (2024)
Abstract Cognitive decline in Parkinson's disease (PD) varies widely. While models to predict cognitive progression exist, comparing traditional probabilistic models to deep learning methods remains understudied. This study compares sequential modeli
Externí odkaz:
https://doaj.org/article/52ded0f1e59b42f580b3cb84a12a40d1
Using massive datasets to train large-scale models has emerged as a dominant approach for broad generalization in natural language and vision applications. In reinforcement learning, however, a key challenge is that available data of sequential decis
Externí odkaz:
http://arxiv.org/abs/2211.13337
Autor:
Romain Beaubois, Jérémy Cheslet, Tomoya Duenki, Giuseppe De Venuto, Marta Carè, Farad Khoyratee, Michela Chiappalone, Pascal Branchereau, Yoshiho Ikeuchi, Timothée Levi
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological diso
Externí odkaz:
https://doaj.org/article/8d9e6586800b4af9ae46bbd8e06dcf9a
Autor:
Venuto Adriana
Publikováno v:
Dados: Revista de Ciências Sociais, Vol 42, Iss 4, Pp 761-801 (1999)
The article studies the process of institutionalization of the profession of astrologer, based on an analysis of the struggle of different professional groups to legitimize new ways of thinking and of organizing their field. Two groups have stood out
Externí odkaz:
https://doaj.org/article/1e1ed760d70146f0ba9536f6dba182ac
Autor:
Pompili, Enrico, Zaccherini, Giacomo, Piano, Salvatore, Toniutto, Pierluigi, Lombardo, Antonio, Gioia, Stefania, Iannone, Giulia, De Venuto, Clara, Tonon, Marta, Gagliardi, Roberta, Baldassarre, Maurizio, Tedesco, Greta, Bedogni, Giorgio, Domenicali, Marco, Di Marco, Vito, Nardelli, Silvia, Calvaruso, Vincenza, Bitetto, Davide, Angeli, Paolo, Caraceni, Paolo
Publikováno v:
In JHEP Reports December 2024 6(12)
Reasoning about the future -- understanding how decisions in the present time affect outcomes in the future -- is one of the central challenges for reinforcement learning (RL), especially in highly-stochastic or partially observable environments. Whi
Externí odkaz:
http://arxiv.org/abs/2108.02096
Autor:
Symons, Teresa, Zemcov, Michael, Bock, James, Cheng, Yun-Ting, Crill, Brendan, Hirata, Christopher, Venuto, Stephanie
Publikováno v:
ApJS 252:24 (2021)
Point-spread function (PSF) estimation in spatially undersampled images is challenging because large pixels average fine-scale spatial information. This is problematic when fine-resolution details are necessary, as in optimal photometry where knowled
Externí odkaz:
http://arxiv.org/abs/2102.01094