Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
---|---|---|---|
1 |
Material Type: Article
|
Brain-Inspired Learning on Neuromorphic SubstratesProceedings of the IEEE, 2021-05, Vol.109 (5), p.935-950 [Peer Reviewed Journal]ISSN: 0018-9219 ;EISSN: 1558-2256 ;DOI: 10.1109/JPROC.2020.3045625 ;CODEN: IEEPADDigital Resources/Online E-Resources |
|
2 |
Material Type: Article
|
Data and Power Efficient Intelligence with Neuromorphic Learning MachinesiScience, 2018-07, Vol.5, p.52-68 [Peer Reviewed Journal]2018 The Author ;Copyright © 2018 The Author. Published by Elsevier Inc. All rights reserved. ;2018 The Author 2018 ;ISSN: 2589-0042 ;EISSN: 2589-0042 ;DOI: 10.1016/j.isci.2018.06.010 ;PMID: 30240646Full text available |
|
3 |
Material Type: Article
|
Stochastic Synapses Enable Efficient Brain-Inspired Learning MachinesFrontiers in neuroscience, 2016-06, Vol.10, p.241-241 [Peer Reviewed Journal]2016. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Copyright © 2016 Neftci, Pedroni, Joshi, Al-Shedivat and Cauwenberghs. 2016 Neftci, Pedroni, Joshi, Al-Shedivat and Cauwenberghs ;ISSN: 1662-4548 ;ISSN: 1662-453X ;EISSN: 1662-453X ;DOI: 10.3389/fnins.2016.00241 ;PMID: 27445650Full text available |
|
4 |
Material Type: Article
|
Visualizing a joint future of neuroscience and neuromorphic engineeringNeuron, 2021-02, Vol.109 (4), p.571-575 [Peer Reviewed Journal]Copyright © 2021. ;Copyright Elsevier Limited Feb 17, 2021 ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0896-6273 ;EISSN: 1097-4199 ;DOI: 10.1016/j.neuron.2021.01.009 ;PMID: 33600754Full text available |
|
5 |
Material Type: Article
|
Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning MachinesFrontiers in neuroscience, 2017-06, Vol.11, p.324-324 [Peer Reviewed Journal]2017. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Copyright © 2017 Neftci, Augustine, Paul and Detorakis. 2017 Neftci, Augustine, Paul and Detorakis ;ISSN: 1662-4548 ;ISSN: 1662-453X ;EISSN: 1662-453X ;DOI: 10.3389/fnins.2017.00324 ;PMID: 28680387Full text available |
|
6 |
Material Type: Book
|
Spiking Neural Network Learning, Benchmarking, Programming and ExecutingISBN: 9782889637676 ;ISBN: 2889637670 ;DOI: 10.3389/978-2-88963-767-6Full text available |
|
7 |
Material Type: Article
|
Memory-Efficient Synaptic Connectivity for Spike-Timing- Dependent PlasticityFrontiers in neuroscience, 2019-04, Vol.13, p.357-357 [Peer Reviewed Journal]2019. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Copyright © 2019 Pedroni, Joshi, Deiss, Sheik, Detorakis, Paul, Augustine, Neftci and Cauwenberghs. 2019 Pedroni, Joshi, Deiss, Sheik, Detorakis, Paul, Augustine, Neftci and Cauwenberghs ;ISSN: 1662-4548 ;ISSN: 1662-453X ;EISSN: 1662-453X ;DOI: 10.3389/fnins.2019.00357 ;PMID: 31110470Full text available |
|
8 |
Material Type: Article
|
Reinforcement learning in artificial and biological systemsNature machine intelligence, 2019-03, Vol.1 (3), p.133-143 [Peer Reviewed Journal]This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2019. ;ISSN: 2522-5839 ;EISSN: 2522-5839 ;DOI: 10.1038/s42256-019-0025-4Full text available |
|
9 |
Material Type: Article
|
Training Spiking Neural Networks Using Lessons From Deep LearningProceedings of the IEEE, 2023-09, Vol.111 (9), p.1016-1054 [Peer Reviewed Journal]ISSN: 0018-9219 ;EISSN: 1558-2256 ;DOI: 10.1109/JPROC.2023.3308088 ;CODEN: IEEPADDigital Resources/Online E-Resources |
|
10 |
Material Type: Article
|
PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systemsFrontiers in neuroinformatics, 2014-08, Vol.8, p.73-73 [Peer Reviewed Journal]2014. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Copyright © 2014 Stefanini, Neftci, Sheik and Indiveri. 2014 ;ISSN: 1662-5196 ;EISSN: 1662-5196 ;EISSN: 1662-453X ;DOI: 10.3389/fninf.2014.00073 ;PMID: 25232314Full text available |
|
11 |
Material Type: Article
|
Meta-learning spiking neural networks with surrogate gradient descentNeuromorphic computing and engineering, 2022-12, Vol.2 (4), p.44002 [Peer Reviewed Journal]2022 The Author(s). Published by IOP Publishing Ltd ;ISSN: 2634-4386 ;EISSN: 2634-4386 ;DOI: 10.1088/2634-4386/ac8828 ;CODEN: NCEECNFull text available |
|
12 |
Material Type: Article
|
On-Chip Error-Triggered Learning of Multi-Layer Memristive Spiking Neural NetworksISSN: 2156-3357 ;EISSN: 2156-3365 ;DOI: 10.1109/jetcas.2020.3040248 ;DOI: 10.5167/uzh-200399Digital Resources/Online E-Resources |
|
13 |
Material Type: Article
|
Dynamic state and parameter estimation applied to neuromorphic systemsISSN: 0899-7667 ;EISSN: 1530-888X ;DOI: 10.5167/uzh-75345 ;DOI: 10.1162/NECO_a_00293Digital Resources/Online E-Resources |
|
14 |
Material Type: Article
|
PyNCS: A microkernel for high-level definition and configuration of neuromorphic electronic systemsCreative Commons: Attribution 3.0 Unported (CC BY 3.0) http://creativecommons.org/licenses/by/3.0 ;ISSN: 1662-5196 ;EISSN: 1662-5196 ;DOI: 10.5167/uzh-107849 ;DOI: 10.3389/fninf.2014.00073Full text available |
|
15 |
Material Type: Article
|
Brain-Inspired Learning on Neuromorphic SubstratesarXiv.org, 2020-102020. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2010.11931Full text available |
|
16 |
Material Type: Conference Proceeding
|
Overcoming phase-change material non-idealities by meta-learning for adaptation on the edgeDOI: 10.29363/nanoge.neumatdecas.2023.043 ;DOI: 10.5167/uzh-254205Digital Resources/Online E-Resources |
|
17 |
Material Type: Article
|
ETLP: Event-based Three-factor Local Plasticity for online learning with neuromorphic hardwarearXiv.org, 2023-012023. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2301.08281Full text available |
|
18 |
Material Type: Article
|
Surrogate Gradient Learning in Spiking Neural NetworksarXiv.org, 2019-052019. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.1901.09948Full text available |
|
19 |
Material Type: Article
|
On-Chip Error-triggered Learning of Multi-layer Memristive Spiking Neural NetworksarXiv.org, 2020-112020. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2011.10852Full text available |
|
20 |
Material Type: Conference Proceeding
|
Error-triggered Three-Factor Learning Dynamics for Crossbar ArraysISBN: 1728149223 ;ISBN: 9781728149226 ;DOI: 10.1109/aicas48895.2020.9073998 ;DOI: 10.5167/uzh-200398Digital Resources/Online E-Resources |