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Equilibrium Propagation (EP) is a biologically-inspired algorithm for convergent RNNs with a local learning rule that comes with strong theoretical guarantees.
Phd thesis: Modeles connexionnistes de l’apprentissage (connectionist learning models)
Y. Lecun · 1987
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Backpropagation without weight transport
J. F. Kolen and J. B. Pollack · 1994
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The graph neural network model
F. Scarselli, M. Gori, A. C. Tsoi, M. Hagenbuchner, and G. Monfardini · 2008
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Learning multiple layers of features from tiny images
A. Krizhevsky, G. Hinton, et al · 2009
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How auto-encoders could provide credit assignment in deep networks via target propagation
Y. Bengio · 2014
Earlier work this paper cites.
Dropout: a simple way to prevent neural networks from overfitting
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 2014
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
K. He, X. Zhang, S. Ren, and J. Sun · 2015
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Random synaptic feedback weights support error backpropagation for deep learning
T. P. Lillicrap, D. Cownden, D. B. Tweed, and C. J. Akerman · 2016
Earlier work this paper cites.
Sgdr: Stochastic gradient descent with warm restarts
I. Loshchilov and F. Hutter · 2016
Earlier work this paper cites.
Automatic differentiation in pytorch
A. Paszke, S. Gross, S. Chintala, G. Chanan, E. Yang, Z. DeVito, Z. Lin, A. Desmaison, L. Antiga, and A. Lerer · 2017
Cited alongside, same era.
Equilibrium propagation: Bridging the gap between energy-based models and backpropagation
B. Scellier and Y. Bengio · 2017
Cited alongside, same era.
Equivalent-accuracy accelerated neural-network training using analogue memory
S. Ambrogio, P. Narayanan, H. Tsai, R. M. Shelby, I. Boybat, C. di Nolfo, S. Sidler, M. Giordano, M. Bodini, N. C. Farinha, et al · 2018
Cited alongside, same era.
Assessing the scalability of biologically-motivated deep learning algorithms and architectures
S. Bartunov, A. Santoro, B. Richards, L. Marris, G. E. Hinton, and T. Lillicrap · 2018
Cited alongside, same era.
In-memory and error-immune differential rram implementation of binarized deep neural networks
M. Bocquet, T. Hirztlin, J.-O. Klein, E. Nowak, E. Vianello, J.-M. Portal, and D. Querlioz · 2018
Cited alongside, same era.
Deep learning without weight transport
M. Akrout, C. Wilson, P. Humphreys, T. Lillicrap, and D. B. Tweed · 2019
Later among the works it cites.
Updates of equilibrium prop match gradients of backprop through time in an rnn with static input
M. Ernoult, J. Grollier, D. Querlioz, Y. Bengio, and B. Scellier · 2019
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Training a spiking neural network with equilibrium propagation
P. O’Connor, E. Gavves, and M. Welling · 2019
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A deep learning framework for neuroscience
B. A. Richards, T. P. Lillicrap, P. Beaudoin, Y. Bengio, R. Bogacz, A. Christensen, C. Clopath, R. P. Costa, A. de Berker, S. Ganguli, et al · 2019
Later among the works it cites.
Equivalence of equilibrium propagation and recurrent backpropagation
B. Scellier and Y. Bengio · 2019
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Initialized equilibrium propagation for backprop-free training
P. O’Connor, E. Gavves, and M. Welling · 2018
Cited alongside, same era.
Vowel recognition with four coupled spin-torque nano-oscillators
M. Romera, P. Talatchian, S. Tsunegi, F. A. Araujo, V. Cros, P. Bortolotti, J. Trastoy, K. Yakushiji, A. Fukushima, H. Kubota, et al · 2018
Cited alongside, same era.
Generalization of equilibrium propagation to vector field dynamics
B. Scellier, A. Goyal, J. Binas, T. Mesnard, and Y. Bengio · 2018
Cited alongside, same era.
Biologically-plausible learning algorithms can scale to large datasets
W. Xiao, H. Chen, Q. Liao, and T. Poggio · 2018
Cited alongside, same era.
M. Ernoult, J. Grollier, D. Querlioz, Y. Bengio, and B. Scellier · 2020
Closest in time.
Backpropagation and the brain
T. P. Lillicrap, A. Santoro, L. Marris, C. J. Akerman, and G. Hinton · 2020
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Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits
A. Payeur, J. Guerguiev, F. Zenke, B. Richards, and R. Naud · 2020
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Equilibrium propagation for memristor-based recurrent neural networks
G. Zoppo, F. Marrone, and F. Corinto · 2020
Closest in time.