Denoising without access to clean data using a partitioned autoencoder

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Denoising without access to clean data using a partitioned autoencoder

20 September 2015

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Papers citing "Denoising without access to clean data using a partitioned autoencoder"

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Title
Deep Convolutional Inverse Graphics Network Tejas D. Kulkarni William F. Whitney Pushmeet Kohli J. Tenenbaum DRL BDL 103 929 0 11 Mar 2015
An Analysis of Unsupervised Pre-training in Light of Recent Advances T. Paine Pooya Khorrami Wei Han Thomas S. Huang SSL 71 56 0 20 Dec 2014
Discovering Hidden Factors of Variation in Deep Networks Brian Cheung J. Livezey Arjun K. Bansal Bruno A. Olshausen DRL 85 193 0 20 Dec 2014
Zero-bias autoencoders and the benefits of co-adapting features K. Konda Roland Memisevic David M. Krueger AI4CE 80 92 0 13 Feb 2014
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks Andrew M. Saxe James L. McClelland Surya Ganguli ODL 178 1,849 0 20 Dec 2013
Improved multiple birdsong tracking with distribution derivative method and Markov renewal process clustering D. Stowell Saso Musevic J. Bonada Mark D. Plumbley 52 13 0 14 Feb 2013
ADADELTA: An Adaptive Learning Rate Method Matthew D. Zeiler ODL 155 6,625 0 22 Dec 2012
Theano: new features and speed improvements Frédéric Bastien Pascal Lamblin Razvan Pascanu James Bergstra Ian Goodfellow Arnaud Bergeron Nicolas Bouchard David Warde-Farley Yoshua Bengio 94 1,420 0 23 Nov 2012
Segregating event streams and noise with a Markov renewal process model D. Stowell Mark D. Plumbley 55 23 0 13 Nov 2012