Zobrazeno 1 - 10
of 15
pro vyhledávání: '"StanisŁaw Woźniak"'
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
Publikováno v:
Frontiers in Neurorobotics, Vol 18 (2024)
Optical identification is often done with spatial or temporal visual pattern recognition and localization. Temporal pattern recognition, depending on the technology, involves a trade-off between communication frequency, range, and accurate tracking.
Externí odkaz:
https://doaj.org/article/954e0c6834b044c4be0f9a7efe7f7923
Autor:
Giorgia Dellaferrera, Stanisław Woźniak, Giacomo Indiveri, Angeliki Pantazi, Evangelos Eleftheriou
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-14 (2022)
Tasks involving continual learning and adaptation to real-time scenarios remain challenging for artificial neural networks in contrast to real brain. The authors propose here a brain-inspired optimizer based on mechanisms of synaptic integration and
Externí odkaz:
https://doaj.org/article/f8bf7e0f3ba948f99cc4f6e3ddb692c0
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:
Martin M. Frank, Ning Li, Malte J. Rasch, Shubham Jain, Ching-Tzu Chen, Ramachandran Muralidhar, Jin-Ping Han, Vijay Narayanan, Timothy M. Philip, Kevin Brew, Andrew Simon, Iqbal Saraf, Nicole Saulnier, Irem Boybat, StanisŁaw Woźniak, Abu Sebastian, Pritish Narayanan, Charles Mackin, An Chen, Hsinyu Tsai, Geoffrey W. Burr
Publikováno v:
2023 IEEE International Reliability Physics Symposium (IRPS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ee13f7463dec77cc87c8b25a122d05c
https://doi.org/10.1109/irps48203.2023.10117874
https://doi.org/10.1109/irps48203.2023.10117874
Publikováno v:
Nature Machine Intelligence. 2:325-336
Spiking neural networks (SNNs) incorporating biologically plausible neurons hold great promise because of their unique temporal dynamics and energy efficiency. However, SNNs have developed separately from artificial neural networks (ANNs), limiting t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8cacb5d5d9916d8411eab9834ba7394
https://doi.org/10.1038/s42256-020-0187-0
https://doi.org/10.1038/s42256-020-0187-0
Autor:
Piotr Miłkowski, Marcin Gruza, Przemysław Kazienko, Joanna Szołomicka, Stanisław Woźniak, Jan Kocoń
Publikováno v:
Computational Collective Intelligence ISBN: 9783031160134
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb875ea1b64359c844b5f2d6ebb6eb55
https://doi.org/10.1007/978-3-031-16014-1_14
https://doi.org/10.1007/978-3-031-16014-1_14
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
Publikováno v:
Nanotechnology. 27(35)
In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::721763a2273e6600771142030c3dc4ab
https://pubmed.ncbi.nlm.nih.gov/27455898
https://pubmed.ncbi.nlm.nih.gov/27455898