Zobrazeno 1 - 10
of 1 907
pro vyhledávání: '"Jens, E."'
Autor:
Abreu, Steven, Pedersen, Jens E.
The value of brain-inspired neuromorphic computers critically depends on our ability to program them for relevant tasks. Currently, neuromorphic hardware often relies on machine learning methods adapted from deep learning. However, neuromorphic compu
Externí odkaz:
http://arxiv.org/abs/2410.22352
In the quest for next-generation sequence modeling architectures, State Space Models (SSMs) have emerged as a potent alternative to transformers, particularly for their computational efficiency and suitability for dynamical systems. This paper invest
Externí odkaz:
http://arxiv.org/abs/2406.09477
Autor:
Pedersen, Jens E., Abreu, Steven, Jobst, Matthias, Lenz, Gregor, Fra, Vittorio, Bauer, Felix C., Muir, Dylan R., Zhou, Peng, Vogginger, Bernhard, Heckel, Kade, Urgese, Gianvito, Shankar, Sadasivan, Stewart, Terrence C., Sheik, Sadique, Eshraghian, Jason K.
Publikováno v:
Nat Commun 15, 8122 (2024)
Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine Learning. Despite a well-established mathematical foundation for neur
Externí odkaz:
http://arxiv.org/abs/2311.14641
Autor:
Razumov, Aleksandr, Heebøll, Holger R., Dummont, Mario, Terra, Osama, Dong, Bozhang, Riebesehl, Jasper, Varming, Poul, Pedersen, Jens E., Da Ros, Francesco, Bowers, John E., Zibar, Darko
Advanced digital signal processing techniques in combination with ultra-wideband balanced coherent detection have enabled a new generation of ultra-high speed fiber-optic communication systems, by moving most of the processing functionalities into di
Externí odkaz:
http://arxiv.org/abs/2305.08681
Autor:
Jens E. Pedersen, Steven Abreu, Matthias Jobst, Gregor Lenz, Vittorio Fra, Felix Christian Bauer, Dylan Richard Muir, Peng Zhou, Bernhard Vogginger, Kade Heckel, Gianvito Urgese, Sadasivan Shankar, Terrence C. Stewart, Sadique Sheik, Jason K. Eshraghian
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine Learning. Despite a well-established mathematical foundation
Externí odkaz:
https://doaj.org/article/31b61ff6c22042c0a55ec54f03b8f39b
