Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Adolfi, Federico"'
Many proposed applications of neural networks in machine learning, cognitive/brain science, and society hinge on the feasibility of inner interpretability via circuit discovery. This calls for empirical and theoretical explorations of viable algorith
Externí odkaz:
http://arxiv.org/abs/2410.08025
Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
Inner Interpretability is a promising emerging field tasked with uncovering the inner mechanisms of AI systems, though how to develop these mechanistic theories is still much debated. Moreover, recent critiques raise issues that question its usefulne
Externí odkaz:
http://arxiv.org/abs/2406.01352
Autor:
Biscione, Valerio, Yin, Dong, Malhotra, Gaurav, Dujmovic, Marin, Montero, Milton L., Puebla, Guillermo, Adolfi, Federico, Heaton, Rachel F., Hummel, John E., Evans, Benjamin D., Habashy, Karim, Bowers, Jeffrey S.
Multiple benchmarks have been developed to assess the alignment between deep neural networks (DNNs) and human vision. In almost all cases these benchmarks are observational in the sense they are composed of behavioural and brain responses to naturali
Externí odkaz:
http://arxiv.org/abs/2404.05290
Publikováno v:
Neural Networks, 162, 199-211 (2023)
Natural and artificial audition can in principle acquire different solutions to a given problem. The constraints of the task, however, can nudge the cognitive science and engineering of audition to qualitatively converge, suggesting that a closer mut
Externí odkaz:
http://arxiv.org/abs/2204.03740
Computational feasibility is a widespread concern that guides the framing and modeling of biological and artificial intelligence. The specification of cognitive system capacities is often shaped by unexamined intuitive assumptions about the search sp
Externí odkaz:
http://arxiv.org/abs/2201.13106
Autor:
Harrison, Peter M. C., Marjieh, Raja, Adolfi, Federico, van Rijn, Pol, Anglada-Tort, Manuel, Tchernichovski, Ofer, Larrouy-Maestri, Pauline, Jacoby, Nori
A core problem in cognitive science and machine learning is to understand how humans derive semantic representations from perceptual objects, such as color from an apple, pleasantness from a musical chord, or seriousness from a face. Markov Chain Mon
Externí odkaz:
http://arxiv.org/abs/2008.02595
Autor:
Bowers, Jeffrey S., Malhotra, Gaurav, Adolfi, Federico, Dujmović, Marin, Montero, Milton L., Biscione, Valerio, Puebla, Guillermo, Hummel, John H., Heaton, Rachel F.
Publikováno v:
In Cognitive Systems Research December 2023 82
Publikováno v:
In Neural Networks May 2023 162:199-211
Autor:
Adolfi, Federico1,2 (AUTHOR) fedeadolfi@gmail.com, Wareham, Todd3 (AUTHOR), van Rooij, Iris4,5,6 (AUTHOR)
Publikováno v:
Topics in Cognitive Science. Apr2023, Vol. 15 Issue 2, p255-273. 19p.
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