Zobrazeno 1 - 10
of 151
pro vyhledávání: '"Giovanni, Cherubini"'
Autor:
Ana Stanojevic, Stanisław Woźniak, Guillaume Bellec, Giovanni Cherubini, Angeliki Pantazi, Wulfram Gerstner
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Communication by rare, binary spikes is a key factor for the energy efficiency of biological brains. However, it is harder to train biologically-inspired spiking neural networks than artificial neural networks. This is puzzling given that th
Externí odkaz:
https://doaj.org/article/232a98336e0941d79563834bb5c1b24e
Autor:
Stanisław Woźniak, Hlynur Jónsson, Giovanni Cherubini, Angeliki Pantazi, Evangelos Eleftheriou
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-9 (2023)
Abstract Visual oddity task was conceived to study universal ethnic-independent analytic intelligence of humans from a perspective of comprehension of spatial concepts. Advancements in artificial intelligence led to important breakthroughs, yet excel
Externí odkaz:
https://doaj.org/article/bf8b556814a54eb58aa4d8ad8b929268
Autor:
Geethan Karunaratne, Manuel Schmuck, Manuel Le Gallo, Giovanni Cherubini, Luca Benini, Abu Sebastian, Abbas Rahimi
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
The implementation of memory-augmented neural networks using conventional computer architectures is challenging due to a large number of read and write operations. Here, Karunaratne, Schmuck et al. propose an architecture that enables analog in-memor
Externí odkaz:
https://doaj.org/article/b553751b28d34003af781f5a72f0719a
Publikováno v:
Neural Computing and Applications. 35:7017-7033
Spiking neural networks (SNNs) are mimicking computationally powerful biologically inspired models in which neurons communicate through sequences of spikes, regarded here as sparse binary sequences of zeros and ones. In neuroscience it is conjectured
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2dd5358785fff9705cbba6f12e5ff6b4
https://doi.org/10.1007/s00521-022-07910-1
https://doi.org/10.1007/s00521-022-07910-1
Autor:
Ana Stanojevic, Stanislaw Wozniak, Guillaume Bellec, Giovanni Cherubini, Angeliki Pantazi, Wulfram Gerstner
Publikováno v:
Proceedings of the Neuromorphic Materials, Devices, Circuits and Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c70c65121802a90aeb6d478ad72ff19
https://doi.org/10.29363/nanoge.neumatdecas.2023.051
https://doi.org/10.29363/nanoge.neumatdecas.2023.051
Publikováno v:
Entropy, Vol 22, Iss 7, p 727 (2020)
Information theory concepts are leveraged with the goal of better understanding and improving Deep Neural Networks (DNNs). The information plane of neural networks describes the behavior during training of the mutual information at various depths bet
Externí odkaz:
https://doaj.org/article/be44bb0302404f4ca8555930ba67fa97
Autor:
Ana Stanojevic, Evangelos Eleftheriou, Giovanni Cherubini, Stanislaw Wozniak, Angeliki Pantazi, Wulfram Gerstner
Publikováno v:
2022 IEEE International Conference on Image Processing (ICIP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d60bdf19c669a551b0f6f546f0e9ef0e
https://doi.org/10.1109/icip46576.2022.9897692
https://doi.org/10.1109/icip46576.2022.9897692
Autor:
Michael Hersche, Geethan Karunaratne, Giovanni Cherubini, Luca Benini, Abu Sebastian, Abbas Rahimi
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Continually learning new classes from fresh data without forgetting previous knowledge of old classes is a very challenging research problem. Moreover, it is imperative that such learning must respect certain memory and computational constraints such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a2ba6f4436aee7bca5f2a45a3d0cc09
https://hdl.handle.net/20.500.11850/580059
https://hdl.handle.net/20.500.11850/580059
Autor:
Sandro Widmer, Marcel Kossel, Giovanni Cherubini, Stanisław Woźniak, Pier Andrea Francese, Ana Stanojevic, Matthias Brändli, Klaus Frick, Angeliki Pantazi
Publikováno v:
IEEE Transactions on Circuits and Systems II: Express Briefs. :1-1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::063015ca6598afd169889f17afee27bb
https://doi.org/10.1109/tcsii.2023.3277784
https://doi.org/10.1109/tcsii.2023.3277784
Autor:
Kartik B. Ariyur, Bahman Gharesifard, Kyriakos G. Vamvoudakis, Christian Ebenbauer, Sophie Tarbouriech, Subhrakanti Dey, Christopher M. Kellett, Paolo Frasca, Giovanni Cherubini, Mireille E. Broucke, Antoine Girard, Usman A. Khan, Martin Guay, Giuseppe Notarstefano, João Manoel Gomes da Silva, Lars Grüne, Luca Scardovi
Publikováno v:
IEEE Control Systems Letters. 4:710-712
Recent advances in machine learning and artificial intelligence have provided astounding performance gains in several domains, including computer vision, natural language processing and recommender systems, in particular when massive data is involved
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::153dbea4b6043d611fd5c18fc5ef9eaf
https://doi.org/10.1109/lcsys.2020.2986590
https://doi.org/10.1109/lcsys.2020.2986590