Zobrazeno 1 - 10
of 161
pro vyhledávání: '"Marra, Giuseppe"'
Autor:
Debot, David, Barbiero, Pietro, Giannini, Francesco, Ciravegna, Gabriele, Diligenti, Michelangelo, Marra, Giuseppe
The lack of transparency in the decision-making processes of deep learning systems presents a significant challenge in modern artificial intelligence (AI), as it impairs users' ability to rely on and verify these systems. To address this challenge, C
Externí odkaz:
http://arxiv.org/abs/2407.15527
Autor:
Dominici, Gabriele, Barbiero, Pietro, Zarlenga, Mateo Espinosa, Termine, Alberto, Gjoreski, Martin, Marra, Giuseppe, Langheinrich, Marc
Causal opacity denotes the difficulty in understanding the "hidden" causal structure underlying the decisions of deep neural network (DNN) models. This leads to the inability to rely on and verify state-of-the-art DNN-based systems, especially in hig
Externí odkaz:
http://arxiv.org/abs/2405.16507
Neuro-symbolic systems (NeSy), which claim to combine the best of both learning and reasoning capabilities of artificial intelligence, are missing a core property of reasoning systems: Declarativeness. The lack of declarativeness is caused by the fun
Externí odkaz:
http://arxiv.org/abs/2405.09521
Autor:
Dominici, Gabriele, Barbiero, Pietro, Giannini, Francesco, Gjoreski, Martin, Marra, Giuseppe, Langheinrich, Marc
Current deep learning models are not designed to simultaneously address three fundamental questions: predict class labels to solve a given classification task (the "What?"), simulate changes in the situation to evaluate how this impacts class predict
Externí odkaz:
http://arxiv.org/abs/2402.01408
Autor:
Barbiero, Pietro, Giannini, Francesco, Ciravegna, Gabriele, Diligenti, Michelangelo, Marra, Giuseppe
The design of interpretable deep learning models working in relational domains poses an open challenge: interpretable deep learning methods, such as Concept-Based Models (CBMs), are not designed to solve relational problems, while relational models a
Externí odkaz:
http://arxiv.org/abs/2308.11991
Autor:
Barbiero, Pietro, Ciravegna, Gabriele, Giannini, Francesco, Zarlenga, Mateo Espinosa, Magister, Lucie Charlotte, Tonda, Alberto, Lio', Pietro, Precioso, Frederic, Jamnik, Mateja, Marra, Giuseppe
Publikováno v:
Proceedings of the 40th International Conference on Machine Learning, PMLR 202:1801-1825, 2023
Deep learning methods are highly accurate, yet their opaque decision process prevents them from earning full human trust. Concept-based models aim to address this issue by learning tasks based on a set of human-understandable concepts. However, state
Externí odkaz:
http://arxiv.org/abs/2304.14068
Autor:
Diligenti, Michelangelo, Giannini, Francesco, Fioravanti, Stefano, Graziani, Caterina, Falaschi, Moreno, Marra, Giuseppe
Knowledge Graph Embeddings (KGE) have become a quite popular class of models specifically devised to deal with ontologies and graph structure data, as they can implicitly encode statistical dependencies between entities and relations in a latent spac
Externí odkaz:
http://arxiv.org/abs/2303.13566
Autor:
De Smet, Lennert, Martires, Pedro Zuidberg Dos, Manhaeve, Robin, Marra, Giuseppe, Kimmig, Angelika, De Raedt, Luc
Neural-symbolic AI (NeSy) allows neural networks to exploit symbolic background knowledge in the form of logic. It has been shown to aid learning in the limited data regime and to facilitate inference on out-of-distribution data. Probabilistic NeSy f
Externí odkaz:
http://arxiv.org/abs/2303.04660
Safe Reinforcement learning (Safe RL) aims at learning optimal policies while staying safe. A popular solution to Safe RL is shielding, which uses a logical safety specification to prevent an RL agent from taking unsafe actions. However, traditional
Externí odkaz:
http://arxiv.org/abs/2303.03226
Autor:
Marra, Giuseppe, Gaynor, Paul, Cantono, Mattia, Kamalov, Valey, Mulholland, Sean, Hill, Ian, Schioppo, Marco, Gaudron, Jacques-Olivier, Edreira, Irene-Barbeito, Clivati, Cecilia, Calonico, Davide
Optical clock comparison via optical fibre links has been achieved over continental scales, but has not yet been demonstrated intercontinentally. The transfer of ultra-stable optical frequencies over transoceanic distances is a challenging task, as t
Externí odkaz:
http://arxiv.org/abs/2212.11150