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pro vyhledávání: '"ZORZI, Marco"'
Autor:
Visalli, Antonino, Calistroni, Francesco Maria, Calderan, Margherita, Donnarumma, Francesco, Zorzi, Marco, Ambrosini, Ettore
Evidence Accumulation Models (EAMs) have been widely used to investigate speeded decision-making processes, but they have largely neglected the role of predictive processes emphasized by theories of the predictive brain. In this paper, we present the
Externí odkaz:
http://arxiv.org/abs/2411.13203
Humans share with many animal species the ability to perceive and approximately represent the number of objects in visual scenes. This ability improves throughout childhood, suggesting that learning and development play a key role in shaping our numb
Externí odkaz:
http://arxiv.org/abs/2409.11028
Humans can readily judge the number of objects in a visual scene, even without counting, and such a skill has been documented in many animal species and babies prior to language development and formal schooling. Numerical judgments are error-free for
Externí odkaz:
http://arxiv.org/abs/2402.03328
Generative neural networks can produce data samples according to the statistical properties of their training distribution. This feature can be used to test modern computational neuroscience hypotheses suggesting that spontaneous brain activity is pa
Externí odkaz:
http://arxiv.org/abs/2305.06745
Publikováno v:
Cognitive Computation, 2022
Deep belief networks (DBNs) are stochastic neural networks that can extract rich internal representations of the environment from the sensory data. DBNs had a catalytic effect in triggering the deep learning revolution, demonstrating for the very fir
Externí odkaz:
http://arxiv.org/abs/2207.05473
Publikováno v:
In Journal of Memory and Language February 2024 134
The ability to accurately predict the surrounding environment is a foundational principle of intelligence in biological and artificial agents. In recent years, a variety of approaches have been proposed for learning to predict the physical dynamics o
Externí odkaz:
http://arxiv.org/abs/1907.13494
Numerosity perception is foundational to mathematical learning, but its computational bases are strongly debated. Some investigators argue that humans are endowed with a specialized system supporting numerical representation; others argue that visual
Externí odkaz:
http://arxiv.org/abs/1907.06996
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Autor:
Lunardon, Maristella, Decarli, Gisella, Sella, Francesco, Lanfranchi, Silvia, Gerola, Silvia, Cossu, Giuseppe, Zorzi, Marco
Publikováno v:
In Research in Developmental Disabilities May 2023 136