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Neural networks (NN) have achieved state-of-the-art performance in various applications.
The greatest of a finite set of random variables
C. E. Clark · 1961
Earlier work this paper cites.
Learning stochastic feedforward networks
R. M. Neal · 1990
Earlier work this paper cites.
A practical Bayesian framework for backprop networks
J. MacKay David · 1992
Earlier work this paper cites.
Keeping the neural networks simple by minimizing the description length of the weights
G. E. Hinton and D. Van Camp · 1993
Earlier work this paper cites.
Bayesian learning for neural networks
R. M. Neal · 1995
Earlier work this paper cites.
Algorithms for non-negative matrix factorization
D. D. Lee and H. S. Seung · 2001
Earlier work this paper cites.
Pattern Recognition and Machine Learning
C. M. Bishop · 2006
Earlier work this paper cites.
Semantic hashing
R. Salakhutdinov and G. E. Hinton · 2009
Earlier work this paper cites.
Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.-A. Manzagol · 2010
Earlier work this paper cites.
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A. Graves · 2011
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C. Wang and D. M. Blei · 2011
Cited alongside, same era.
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Cited alongside, same era.
Beta-negative binomial process and poisson factor analysis
M. Zhou, L. Hannah, D. B. Dunson, and L. Carin · 2012
Cited alongside, same era.
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Cited alongside, same era.
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T. Chen, M. Li, Y. Li, M. Lin, N. Wang, M. Wang, T. Xiao, B. Xu, C. Zhang, and Z. Zhang · 2015
Later among the works it cites.
Deep poisson factor modeling
R. Henao, Z. Gan, J. Lu, and L. Carin · 2015
Later among the works it cites.
Probabilistic backpropagation for scalable learning of Bayesian neural networks
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Later among the works it cites.
Deep visual-semantic alignments for generating image descriptions
A. Karpathy and F. Li · 2015
Later among the works it cites.
Deep exponential families
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Later among the works it cites.
Collaborative deep learning for recommender systems
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SNAP Datasets: Stanford large network dataset collection
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Cited alongside, same era.
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C. Blundell, J. Cornebise, K. Kavukcuoglu, and D. Wierstra · 2015
Cited alongside, same era.
Later among the works it cites.
Deep Learning
I. Goodfellow, Y. Bengio, and A. Courville · 2016
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Towards Bayesian deep learning: A framework and some existing methods
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