Recurrent Networks of Spiking Neurons: From Biology to Novel Computing Technology - Wolfgang Maass
Автор: Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC)
Загружено: 2020-02-19
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By: Wolfgang Maass
Affiliation: Institute for Theoretical Computer Science, Graz University of Technology
Date: 2020-02-19T14:00:00+00:00
Abstract
I will review progress in research on networks of spiking neurons during the last 20 years, from reservoir computing to dramatic recent advances in the context of Deep Learning. I will end with a discussion of currently open research problems.
Background and details can be found in
A. Subramoney, F. Scherr, and W. Maass. Reservoirs learn to learn. arXiv:1909.07486v1, 2019. https://igi-web.tugraz.at/PDF/250.pdf
G. Bellec, D. Salaj, A. Subramoney, R. Legenstein, and W. Maass. Long short-term memory and learning-to-learn in networks of spiking neurons. 32nd Conference on Neural Information Processing Systems (NIPS 2018), Montreal, Canada, 2018. https://igi-web.tugraz.at/PDF/243.pdf
G. Bellec, F. Scherr, A. Subramoney, E. Hajek, D. Salaj, R. Legenstein, and W. Maass. A solution to the learning dilemma for recurrent networks of spiking neurons. bioRxiv/org/10.1101/738385v3, December 2019. https://igi-web.tugraz.at/PDF/248.pdf
 
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