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1
Towards deep learning with segregated dendrites
Towards deep learning with segregated dendrites
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Towards deep learning with segregated dendrites

eLife, 2017-12, Vol.6 [Peer Reviewed Journal]

2017, Guerguiev et al. This work is licensed under the Creative Commons Attribution License ( https://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. ;2017, Guerguiev et al 2017 Guerguiev et al ;ISSN: 2050-084X ;EISSN: 2050-084X ;DOI: 10.7554/eLife.22901 ;PMID: 29205151

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2
Feasibility of dopamine as a vector-valued feedback signal in the basal ganglia
Feasibility of dopamine as a vector-valued feedback signal in the basal ganglia
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Feasibility of dopamine as a vector-valued feedback signal in the basal ganglia

Proceedings of the National Academy of Sciences - PNAS, 2023-08, Vol.120 (32), p.e2221994120-e2221994120 [Peer Reviewed Journal]

Copyright National Academy of Sciences Aug 8, 2023 ;Copyright © 2023 the Author(s). Published by PNAS. 2023 ;ISSN: 0027-8424 ;ISSN: 1091-6490 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.2221994120 ;PMID: 37527344

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3
GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity
GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity
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GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity

Frontiers in computational neuroscience, 2020-11, Vol.14, p.576841-576841 [Peer Reviewed Journal]

2020. 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 © 2020 Zhao, Zeng, Zhang, Shi and Zhao. 2020 Zhao, Zeng, Zhang, Shi and Zhao ;ISSN: 1662-5188 ;EISSN: 1662-5188 ;DOI: 10.3389/fncom.2020.576841 ;PMID: 33281591

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4
Direct Feedback Alignment With Sparse Connections for Local Learning
Direct Feedback Alignment With Sparse Connections for Local Learning
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Direct Feedback Alignment With Sparse Connections for Local Learning

Frontiers in neuroscience, 2019-05, Vol.13, p.525-525 [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 Crafton, Parihar, Gebhardt and Raychowdhury. 2019 Crafton, Parihar, Gebhardt and Raychowdhury ;ISSN: 1662-4548 ;ISSN: 1662-453X ;EISSN: 1662-453X ;DOI: 10.3389/fnins.2019.00525 ;PMID: 31178689

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5
Biologically plausible local synaptic learning rules robustly implement deep supervised learning
Biologically plausible local synaptic learning rules robustly implement deep supervised learning
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Biologically plausible local synaptic learning rules robustly implement deep supervised learning

Frontiers in neuroscience, 2023-10, Vol.17, p.1160899-1160899 [Peer Reviewed Journal]

Copyright © 2023 Konishi, Igarashi and Miura. ;2023. 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 © 2023 Konishi, Igarashi and Miura. 2023 Konishi, Igarashi and Miura ;ISSN: 1662-4548 ;ISSN: 1662-453X ;EISSN: 1662-453X ;DOI: 10.3389/fnins.2023.1160899 ;PMID: 37886676

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6
Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines
Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines
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Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

Frontiers 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: 28680387

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7
Branching into brains
Branching into brains
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Branching into brains

eLife, 2017-12, Vol.6 [Peer Reviewed Journal]

2017, Shai et al. This work is licensed under the Creative Commons Attribution License ( https://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. ;2017, Shai et al 2017 Shai et al ;ISSN: 2050-084X ;EISSN: 2050-084X ;DOI: 10.7554/eLife.33066 ;PMID: 29205152

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8
LAFD: Local-differentially Private and Asynchronous Federated Learning with Direct Feedback Alignment
LAFD: Local-differentially Private and Asynchronous Federated Learning with Direct Feedback Alignment
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LAFD: Local-differentially Private and Asynchronous Federated Learning with Direct Feedback Alignment

IEEE access, 2023-01, Vol.11, p.1-1 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2023.3304704 ;CODEN: IAECCG

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9
Random feedback alignment algorithms to train neural networks: why do they align?
Random feedback alignment algorithms to train neural networks: why do they align?
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Article 		Add to My Research

Random feedback alignment algorithms to train neural networks: why do they align?

Machine learning: science and technology, 2024-06, Vol.5 (2), p.025023 [Peer Reviewed Journal]

2024 The Author(s). Published by IOP Publishing Ltd. This work is published 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. ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/ad3ee5

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10
Hardware-Based Spiking Neural Network Using a TFT-Type AND Flash Memory Array Architecture Based on Direct Feedback Alignment
Hardware-Based Spiking Neural Network Using a TFT-Type AND Flash Memory Array Architecture Based on Direct Feedback Alignment
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Hardware-Based Spiking Neural Network Using a TFT-Type AND Flash Memory Array Architecture Based on Direct Feedback Alignment

IEEE access, 2021, Vol.9, p.73121-73132 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2021.3080310 ;CODEN: IAECCG

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11
Supervised Learning Algorithm Based on Spike Train Inner Product for Deep Spiking Neural Networks
Supervised Learning Algorithm Based on Spike Train Inner Product for Deep Spiking Neural Networks
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Supervised Learning Algorithm Based on Spike Train Inner Product for Deep Spiking Neural Networks

Brain sciences, 2023-01, Vol.13 (2), p.168 [Peer Reviewed Journal]

COPYRIGHT 2023 MDPI AG ;2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2023 by the authors. 2023 ;ISSN: 2076-3425 ;EISSN: 2076-3425 ;DOI: 10.3390/brainsci13020168 ;PMID: 36831711

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12
Leveraging (Physical) Randomness in Machine Learning Algorithms
Leveraging (Physical) Randomness in Machine Learning Algorithms
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Thesises (postgraduate) 		Add to My Research

Leveraging (Physical) Randomness in Machine Learning Algorithms

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