Fetching the paper…
Reading the bibliography…
Revealing hidden features in unlabeled data is called unsupervised feature learning, which plays an important role in pretraining a deep neural network.
Solution of ’Solvable model of a spin glass’
D. J. Thouless, P. W. Anderson, and R. G. Palmer · 1977
Earlier work this paper cites.
Maximum likelihood from incomplete data via the em algorithm
A. P. Dempster, N. M. Laird, and D. B. Rubin · 1977
Earlier work this paper cites.
The simplest spin glass
D.J. Gross and M. Mezard · 1984
Earlier work this paper cites.
Spin glasses with p-spin interactions
E. Gardner · 1985
Earlier work this paper cites.
Storing infinite numbers of patterns in a spin-glass model of neural networks
Daniel J. Amit, Hanoch Gutfreund, and H. Sompolinsky · 1985
Earlier work this paper cites.
Spin Glass Theory and Beyond
M. Mézard, G. Parisi, and M. A. Virasoro · 1987
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner · 1998
Earlier work this paper cites.
Statistical Physics of Spin Glasses and Information Processing: An Introduction
H. Nishimori · 2001
Earlier work this paper cites.
The bethe lattice spin glass revisited
M. Mézard and G. Parisi · 2001
Earlier work this paper cites.
Absence of replica symmetry breaking in a region of the phase diagram of the Ising spin glass
Hidetoshi Nishimori and David Sherrington · 2001
Earlier work this paper cites.
Object Perception as Bayesian Inference
Daniel Kersten, Pascal Mamassian, and Alan Yuille · 2004
Cited alongside, same era.
Spin-glass theory for pedestrians
Tommaso Castellani and Andrea Cavagna · 2005
Cited alongside, same era.
Constructing free energy approximations and generalized belief propagation algorithms
J. S. Yedidia, W. T. Freeman, and Y. Weiss · 2005
Cited alongside, same era.
Reducing the dimensionality of data with neural networks
G. E. Hinton and R. R. Salakhutdinov · 2006
Cited alongside, same era.
A fast learning algorithm for deep belief nets
G Hinton, S Osindero, and Y Teh · 2006
Cited alongside, same era.
Learning multiple layers of representation
Geoffrey E. Hinton · 2007
Cited alongside, same era.
Representation learning: A review and new perspectives
Y. Bengio, A. Courville, and P. Vincent · 2013
Later among the works it cites.
An Iterative Construction of Solutions of the TAP Equations for the Sherrington–Kirkpatrick Model
Erwin Bolthausen · 2014
Later among the works it cites.
Human-level concept learning through probabilistic program induction
Brenden M. Lake, Ruslan Salakhutdinov, and Joshua B. Tenenbaum · 2015
Later among the works it cites.
Weight Uncertainty in Neural Networks
C. Blundell, J. Cornebise, K. Kavukcuoglu, and D. Wierstra · 2015
Later among the works it cites.
Advanced mean-field theory of the restricted boltzmann machine
Haiping Huang and Taro Toyoizumi · 2015
Later among the works it cites.
Binaryconnect: Training deep neural networks with binary weights during propagations
Matthieu Courbariaux, Yoshua Bengio, and Jean-Pierre David · 2015
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Information, Physics, and Computation
M. Mézard and A. Montanari · 2009
Cited alongside, same era.
Message-passing algorithms for compressed sensing
David L. Donoho, Arian Maleki, and Andrea Montanari · 2009
Cited alongside, same era.
Probabilistic reconstruction in compressed sensing: algorithms, phase diagrams, and threshold achieving matrices
Florent Krzakala, Marc Mezard, Francois Sausset, Yifan Sun, and Lenka Zdeborova · 2012
Cited alongside, same era.
Multitasking associative networks
Elena Agliari, Adriano Barra, Andrea Galluzzi, Francesco Guerra, and Francesco Moauro · 2012
Cited alongside, same era.
Later among the works it cites.
Unsupervised feature learning from finite data by message passing: Discontinuous versus continuous phase transition
Haiping Huang and Taro Toyoizumi · 2016
Closest in time.
Statistical physics of inference: thresholds and algorithms
Lenka Zdeborová and Florent Krzakala · 2016
Closest in time.
Mean-field message-passing equations in the hopfield model and its generalizations
Marc Mézard · 2017
Closest in time.