Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Pietro, Barbiero"'
Autor:
Sarah Kidwai, Pietro Barbiero, Irma Meijerman, Alberto Tonda, Paula Perez‐Pardo, Pietro Lio ́, Anke H. van derMaitland‐Zee, Daniel L. Oberski, Aletta D. Kraneveld, Alejandro Lopez‐Rincon
Publikováno v:
Clinical and Translational Allergy, Vol 13, Iss 11, Pp n/a-n/a (2023)
Abstract Background Not being well controlled by therapy with inhaled corticosteroids and long‐acting β2 agonist bronchodilators is a major concern for severe‐asthma patients. The current treatment option for these patients is the use of biologi
Externí odkaz:
https://doaj.org/article/dc82ea5a34754f9ab2041cdf4636cd31
Publikováno v:
Frontiers in Genetics, Vol 12 (2021)
Objective: Modern medicine needs to shift from a wait and react, curative discipline to a preventative, interdisciplinary science aiming at providing personalized, systemic, and precise treatment plans to patients. To this purpose, we propose a “di
Externí odkaz:
https://doaj.org/article/03abdd917dc041f19ef70ae6be23b444
Autor:
Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci
Publikováno v:
Artificial Intelligence
Artificial Intelligence, 2023, 314, pp.103822. ⟨10.1016/j.artint.2022.103822⟩
Artificial Intelligence, 2023, 314, pp.103822. ⟨10.1016/j.artint.2022.103822⟩
International audience; The large and still increasing popularity of deep learning clashes with a major limit of neural network architectures, that consists in their lack of capability in providing human-understandable motivations of their decisions.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be6d72e1626a393d5945b596fb670aa7
https://zenodo.org/record/7584205
https://zenodo.org/record/7584205
Publikováno v:
Machine Learning, Optimization, and Data Science ISBN: 9783030954666
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::df7d1977801256fd7b6f0af6872a93e5
https://doi.org/10.1007/978-3-030-95467-3_29
https://doi.org/10.1007/978-3-030-95467-3_29
Autor:
Mateo Espinosa Zarlenga, Pietro, Barbiero, Gabriele, Ciravegna, Giuseppe, Marra, Giannini, Francesco, Diligenti, Michelangelo, Zohreh, Shams, Frederic, Precioso, Melacci, Stefano, Adrian, Weller, Pietro, Lió, Mateja, Jamnik
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1820::fd1717b6eedb56474028cc76d20bbf60
https://hdl.handle.net/11365/1231237
https://hdl.handle.net/11365/1231237
Publikováno v:
Behavioral Sciences, Vol 8, Iss 3, p 34 (2018)
This study investigates the relationship between the level to which a person feels connected to Nature and that person’s ability to perceive the restorative value of a natural environment. We assume that perceived restorativeness may depend on an i
Externí odkaz:
https://doaj.org/article/ec500b66085a4f02bf60f83d6ec27daa
Recent research on graph neural network (GNN) models successfully applied GNNs to classical graph algorithms and combinatorial optimisation problems. This has numerous benefits, such as allowing applications of algorithms when preconditions are not s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdda24d7e7171a1dc2dceda4957a4205
http://arxiv.org/abs/2107.07493
http://arxiv.org/abs/2107.07493
Publikováno v:
IJCNN
Topological learning is a wide research area aiming at uncovering the mutual spatial relationships between the elements of a set. Some of the most common and oldest approaches involve the use of unsupervised competitive neural networks. However, thes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ea3527553b79c7b283d3b18bee53a2d
http://hdl.handle.net/11583/2927518
http://hdl.handle.net/11583/2927518
Autor:
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Pietro Lió, Marco Gori, Stefano Melacci
Publikováno v:
AAAI
AAAI 2022-36th AAAI conference on artificial intelligence
AAAI 2022-36th AAAI conference on artificial intelligence, AAAI, Feb 2022, Vancouver, United States
HAL
AAAI 2022-36th AAAI conference on artificial intelligence
AAAI 2022-36th AAAI conference on artificial intelligence, AAAI, Feb 2022, Vancouver, United States
HAL
International audience; Explainable artificial intelligence has rapidly emerged since lawmakers have started requiring interpretable models for safety-critical domains. Concept-based neural networks have arisen as explainable-by-design methods as the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::919b10e19c2e3b14059347a82aa73eb8