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Predictive coding networks (PCNs) are an influential model for information processing in the brain.
New tools for prediction and analysis in the behavioral sciences
P. Werbos · 1974
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Learning representations by back-propagating errors
D. E. Rumelhart, G. E. Hinton, and R. J. Williams · 1986
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Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects
R. P. Rao and D. H. Ballard · 1999
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Learning and inference in the brain
K. Friston · 2003
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Equivalence of backpropagation and contrastive Hebbian learning in a layered network
X. Xie and H. S. Seung · 2003
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A theory of cortical responses
K. Friston · 2005
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Predictive coding explains binocular rivalry: An epistemological review
J. Hohwy, A. Roepstorff, and K. Friston · 2008
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Attention, uncertainty, and free energy
H. Feldman and K. Friston · 2010
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Deep supervised, but not unsupervised, models may explain IT cortical representation
S.-M. Khaligh-Razavi and N. Kriegeskorte · 2014
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Cerebral hierarchies: Predictive processing, precision and the pulvinar
R. Kanai, Y. Komura, S. Shipp, and K. Friston · 2015
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Difference target propagation
D.-H. Lee, S. Zhang, A. Fischer, and Y. Bengio · 2015
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Repetition suppression and its contextual determinants in predictive coding
R. Auksztulewicz and K. Friston · 2016
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A theory of local learning, the learning channel, and the optimality of backpropagation
P. Baldi and P. Sadowski · 2016
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Deep predictive coding networks for video prediction and unsupervised learning
W. Lotter, G. Kreiman, and D. Cox · 2016
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Using goal-driven deep learning models to understand sensory cortex
D. Yamins and J. DiCarlo · 2016
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A tutorial on the free-energy framework for modelling perception and learning
R. Bogacz · 2017
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Cortical credit assignment by Hebbian, neuromodulatory and inhibitory plasticity
J. Aljadeff, J. D’amour, R. E. Field, R. C. Froemke, and C. Clopath · 2019
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Biologically plausible deep learning—But how far can we go with shallow networks?
B. Illing, W. Gerstner, and J. Brea · 2019
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Training neural networks with local error signals
A. Nøkland and L. H. Eidnes · 2019
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Biologically motivated algorithms for propagating local target representations
A. G. Ororbia and A. Mali · 2019
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Theories of error back-propagation in the brain
J. C. Whittington and R. Bogacz · 2019
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A. G. Ororbia, P. Haffner, D. Reitter, and C. L. Giles · 2017
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Equilibrium propagation: Bridging the gap between energy-based models and backpropagation
B. Scellier and Y. Bengio · 2017
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A predictive coding account of bistable perception-a model-based fMRI study
V. Weilnhammer, H. Stuke, G. Hesselmann, P. Sterzer, and K. Schmack · 2017
Cited alongside, same era.
An approximation of the error backpropagation algorithm in a predictive coding network with local Hebbian synaptic plasticity
J. C. Whittington and R. Bogacz · 2017
Cited alongside, same era.
A task-optimized neural network replicates human auditory behavior, predicts brain responses, and reveals a cortical processing hierarchy
A. Kell, D. Yamins, E. Shook, S. Norman-Haignere, and J. McDermott · 2018
Cited alongside, same era.
Illusory motion reproduced by deep neural networks trained for prediction
E. Watanabe, A. Kitaoka, K. Sakamoto, M. Yasugi, and K. Tanaka · 2018
Cited alongside, same era.
T. Lillicrap, A. Santoro, L. Marris, C. Akerman, and G. Hinton · 2020
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Predictive coding approximates backprop along arbitrary computation graphs
B. Millidge, A. Tschantz, and C. L. Buckley · 2020
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The singular values of convolutional layers
A. Sedghi, V. Gupta, and P. Long · 2020
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Can the brain do backpropagation?—exact implementation of backpropagation in predictive coding networks
Y. Song, T. Lukasiewicz, Z. Xu, and R. Bogacz · 2020
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Supervised learning in spiking neural networks: A review of algorithms and evaluations
X. Wang, X. Lin, and X. Dang · 2020
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