Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Mattia Rigotti"'
Autor:
Stefano Recanatesi, Matthew Farrell, Guillaume Lajoie, Sophie Deneve, Mattia Rigotti, Eric Shea-Brown
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-13 (2021)
Neural networks trained using predictive models generate representations that recover the underlying low-dimensional latent structure in the data. Here, the authors demonstrate that a network trained on a spatial navigation task generates place-relat
Externí odkaz:
https://doaj.org/article/411ac526db244399bdd114924abfd060
Publikováno v:
Frontiers in Neuroscience, Vol 13 (2019)
Analog arrays are a promising emerging hardware technology with the potential to drastically speed up deep learning. Their main advantage is that they employ analog circuitry to compute matrix-vector products in constant time, irrespective of the siz
Externí odkaz:
https://doaj.org/article/27a1a5f424354fe6a98bf2c708b3018b
Publikováno v:
Frontiers in Computational Neuroscience, Vol 4 (2010)
Neural activity of behaving animals, especially in the prefrontal cortex, is highly heterogeneous, with selective responses to diverse aspects of the executed task. We propose a general model of recurrent neural networks that perform complex rule-bas
Externí odkaz:
https://doaj.org/article/0e83e420f9b94378b87b841f08afc237
Autor:
Pierre Dognin, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young, Brian Belgodere
Publikováno v:
Journal of Artificial Intelligence Research. 73:437-459
Image captioning has recently demonstrated impressive progress largely owing to the introduction of neural network algorithms trained on curated dataset like MS-COCO. Often work in this field is motivated by the promise of deployment of captioning sy
Autor:
Thomas Frick, Diego Antognini, Mattia Rigotti, Ioana Giurgiu, Benjamin Grewe, Cristiano Malossi
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031250811
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc795f7197585cdb8c733a444c35d2fc
https://doi.org/10.1007/978-3-031-25082-8_19
https://doi.org/10.1007/978-3-031-25082-8_19
Autor:
Brian Belgodere, Vijil Chenthamarakshan, Payel Das, Pierre Dognin, Toby Kurien, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783031264214
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::292c730b202c06e0df3997edb8a65397
https://doi.org/10.1007/978-3-031-26422-1_47
https://doi.org/10.1007/978-3-031-26422-1_47
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031250811
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7526f7579ee435e99fbb70d5f92bbfc7
https://doi.org/10.1007/978-3-031-25082-8_16
https://doi.org/10.1007/978-3-031-25082-8_16
Autor:
Zhu, R., Mattia Rigotti
Publikováno v:
Scopus-Elsevier
The Q-learning algorithm is known to be affected by the maximization bias, i.e. the systematic overestimation of action values, an important issue that has recently received renewed attention. Double Q-learning has been proposed as an efficient algor
Autor:
Guillaume Lajoie, Matthew Farrell, Eric Shea-Brown, Sophie Denève, Mattia Rigotti, Stefano Recanatesi
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-13 (2021)
Nature Communications
Nature Communications
Artificial neural networks have recently achieved many successes in solving sequential processing and planning tasks. Their success is often ascribed to the emergence of the task’s low-dimensional latent structure in the network activity – i.e.,
Autor:
Andrea Bartezzaghi, Ioana Giurgiu, Chiara Marchiori, Mattia Rigotti, Rizal Sebastian, Cristiano Malossi
Publikováno v:
2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON).