Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible

Generalization and information storage in networks of adaline “neurons”

Widrow, B. (1962) · 1962

Earlier work this paper cites.

Boltzmann machines: Constraint satisfaction networks that learn

Hinton, G. E., Sejnowski, T. J., and Ackley, D. H. (1984) · 1984

Earlier work this paper cites.

Neurons with graded responses have collective computational properties like those of two-state neurons

Hopfield, J. J. (1984) · 1984

Earlier work this paper cites.

A learning rule for asynchronous perceptrons with feedback in a combinatorial environment

Almeida, L. B. (1987) · 1987

Earlier work this paper cites.

Learning representations by recirculation

Hinton, G. E. and McClelland, J. L. (1988) · 1987

Earlier work this paper cites.

Generalization of back-propagation to recurrent neural networks

Pineda, F. J. (1987) · 1987

Earlier work this paper cites.

Different voltage-dependent thresholds for inducing long-term depression and long-term potentiation in slices of rat visual cortex

Artola, A., Brocher, S., and Singer, W. (1990) · 1990

Earlier work this paper cites.

Learning continuous probability distributions with the contrastive Hebbian algorithm

Movellan, J. R. and McClelland, J. L. (1991) · 1991

Earlier work this paper cites.

Regulation of synaptic efficacy by coincidence of postsynaptic aps and epsps

Markram, H., Lübke, J., Frotscher, M., and Sakmann, B. (1997) · 1997

Earlier work this paper cites.

The variable discharge of cortical neurons: implications for connectivity, computation, and information coding

Shadlen, M. N. and Newsome, W. T. (1998) · 1998

Cited alongside, same era.

Rate, timing, and cooperativity jointly determine cortical synaptic plasticity

Sjöström, P. J., Turrigiano, G. G., and Nelson, S. B. (2001) · 2001

Cited alongside, same era.

The high-conductance state of neocortical neurons in vivo

Destexhe, A., Rudolph, M., and Paré, D. (2003) · 2003

Cited alongside, same era.

Equivalence of backpropagation and contrastive Hebbian learning in a layered network

Xie, X. and Seung, H. S. (2003) · 2003

Cited alongside, same era.

Biophysics of computation: information processing in single neurons

Koch, C. (2004) · 2004

Cited alongside, same era.

A fast learning algorithm for deep belief nets

Hinton, G. E., Osindero, S., and Teh, Y. (2006) · 2006

Matching recall and storage in sequence learning with spiking neural networks

Brea, J., Senn, W., and Pfister, J.-P. (2013) · 2013

Later among the works it cites.

A cellular mechanism for cortical associations: an organizing principle for the cerebral cortex

Larkum, M. (2013) · 2013

Later among the works it cites.

Backprop-free auto-encoders

Lee, D.-H. and Bengio, Y. (2014) · 2014

Later among the works it cites.

Learning by the dendritic prediction of somatic spiking

Urbanczik, R. and Senn, W. (2014) · 2014

Later among the works it cites.

Early inference in energy-based models approximates back-propagation

Original

Bengio, Y. and Fischer, A. (2015) · 2015

Later among the works it cites.

Difference target propagation

Lee, D.-H., Zhang, S., Fischer, A., and Bengio, Y. (2015) · 2015