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Current algorithms for deep learning probably cannot run in the brain because they rely on weight transport, where forward-path neurons transmit their synaptic weights to a feedback path, in a way that is likely impossible biologically.
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Yann LeCun, Bernhard Boser, John S Denker, Donnie Henderson, Richard E Howard, Wayne Hubbard, and Lawrence D Jackel · 1989
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Nathan Intrator and Leon N Cooper · 1992
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Backpropagation without weight transport
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The Neurology of Eye Movements
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Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems
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Gina G Turrigiano · 2008
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On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George E Dahl, and Geoffrey E Hinton · 2013
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Robert Urbanczik and Walter Senn · 2014
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Sergey Ioffe and Christian Szegedy · 2015
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Total wiring length minimization of
Andrey Gushchin and Ao Tang · 2015
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The developmental rules of neural superposition in
Marion Langen, Egemen Agi, Dylan J Altschuler, Lani F Wu, Steven J Altschuler, and Peter Robin Hiesinger · 2015
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Random synaptic feedback weights support error backpropagation for deep learning
Timothy P Lillicrap, Daniel Cownden, Douglas B Tweed, and Colin J Akerman · 2016
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Biologically feasible deep learning with segregated dendrites
Feedback alignment in deep convolutional networks
Theodore H Moskovitz, Ashok Litwin-Kumar, and LF Abbott · 2018
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Biologically-plausible learning algorithms can scale to large datasets
Will Xiao, Honglin Chen, Qianli Liao, and Tomaso Poggio · 2018
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Homeostatic synaptic scaling: Molecular regulators of synaptic AMPA-type glutamate receptors
Dhrubajyoti Chowdhury and Johannes W Hell · 2018
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Maestro: An open-source infrastructure for modeling dataflows within deep learning accelerators
Hyoukjun Kwon, Michael Pellauer, and Tushar Krishna · 2018
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Sparse bursts optimize information transmission in a multiplexed neural code
Richard Naud and Henning Sprekeler · 2018
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Jordan Guergiuev, Timothy P Lillicrap, and Blake A Richards · 2016
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Jordan Guerguiev, Timothy P Lillicrap, and Blake A Richards · 2017
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Assessing the scalability of biologically-motivated deep learning algorithms and architectures
Sergey Bartunov, Adam Santoro, Blake Richards, Luke Marris, Geoffrey E Hinton, and Timothy Lillicrap · 2018
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