Navigation auf zora.uzh.ch
Frenkel, Charlotte (2021). Sparsity provides a competitive advantage. Nature Machine Intelligence, 3(9):742-743.
Neuromorphic chips that use spikes to encode information could provide fast and energy-efficient computing for ubiquitous embedded systems. A bio-plausible spike-timing solution for training spiking neural networks that makes the most of sparsity is implemented on the BrainScaleS-2 hardware platform.
| Item Type: | Journal Article, refereed, further contribution |
|---|---|
| Communities & Collections: | 07 Faculty of Science > Institute of Neuroinformatics |
| Dewey Decimal Classification: | 570 Life sciences; biology |
| Scopus Subject Areas: | Physical Sciences > Software
Physical Sciences > Human-Computer Interaction Physical Sciences > Computer Vision and Pattern Recognition Physical Sciences > Computer Networks and Communications Physical Sciences > Artificial Intelligence |
| Uncontrolled Keywords: | Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Human-Computer Interaction, Software |
| Language: | English |
| Date: | 1 September 2021 |
| Deposited On: | 16 Mar 2022 09:57 |
| Last Modified: | 27 Dec 2024 02:39 |
| Publisher: | Nature Publishing Group |
| ISSN: | 2522-5839 |
| OA Status: | Closed |
| Publisher DOI: | https://doi.org/10.1038/s42256-021-00387-y |
Frenkel, Charlotte