On the achievability of blind source separation for high-dimensional
nonlinear source mixtures

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On the achievability of blind source separation for high-dimensional nonlinear source mixtures

2 August 2018

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Papers citing "On the achievability of blind source separation for high-dimensional nonlinear source mixtures"

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Title
Dimensionality reduction to maximize prediction generalization capability Takuya Isomura Taro Toyoizumi 32 17 0 01 Mar 2020
Variational Autoencoders and Nonlinear ICA: A Unifying Framework Ilyes Khemakhem Diederik P. Kingma Ricardo Pio Monti Aapo Hyvarinen OOD 73 598 0 10 Jul 2019
Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes Lei Wu Zhanxing Zhu E. Weinan ODL 67 221 0 30 Jun 2017
Provable benefits of representation learning Sanjeev Arora Andrej Risteski SSL 35 12 0 14 Jun 2017
Blind nonnegative source separation using biological neural networks Cengiz Pehlevan S. Mohan D. Chklovskii 115 39 0 01 Jun 2017
The loss surface of deep and wide neural networks Quynh N. Nguyen Matthias Hein ODL 169 285 0 26 Apr 2017
Depth Creates No Bad Local Minima Haihao Lu Kenji Kawaguchi ODL FAtt 78 121 0 27 Feb 2017
Deep Learning without Poor Local Minima Kenji Kawaguchi ODL 224 927 0 23 May 2016
Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA Aapo Hyvarinen H. Morioka CML OOD AI4TS 77 410 0 20 May 2016
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 131 2,269 0 30 Oct 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 455 16,922 0 20 Dec 2013
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 463 7,667 0 03 Jul 2012