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Nonlinear independent component analysis (ICA) provides an appealing framework for unsupervised feature learning, but the models proposed so far are not identifiable.
Learning invariance from transformation sequences
P. Földiák · 1991
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Independent component analysis—a new concept?
P. Comon · 1994
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Autoencoders, minimum description length, and helmholtz free energy
G. E. Hinton and R. S. Zemel · 1994
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A neural net for blind separation of nonstationary signals
K. Matsuoka, M. Ohya, and M. Kawamoto · 1995
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Fast and robust fixed-point algorithms for independent component analysis
A. Hyvärinen · 1999
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Nonlinear independent component analysis: Existence and uniqueness results
A. Hyvärinen and P. Pajunen · 1999
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Blind source separation by nonstationarity of variance: A cumulant-based approach
A. Hyvärinen · 2001
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Blind separation of instantaneous mixtures of non stationary sources
D.-T. Pham and J.-F. Cardoso · 2001
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Nonlinear blind source separation using a radial basis function network
Y. Tan, J. Wang, and J.M. Zurada · 2001
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Slow feature analysis: Unsupervised learning of invariances
L. Wiskott and T. J. Sejnowski · 2002
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MISEP—linear and nonlinear ICA based on mutual information
L. B. Almeida · 2003
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Kernel-based nonlinear blind source separation
S. Harmeling, A. Ziehe, M. Kawanabe, and K.-R. Müller · 2003
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Learning multiple layers of representation
G. E. Hinton · 2007
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Natural Image Statistics
A. Hyvärinen, J. Hurri, and P. O. Hoyer · 2009
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Deep learning from temporal coherence in video
H. Mobahi, R. Collobert, and J. Weston · 2009
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Understanding the difficulty of training deep feedforward neural networks
X. Glorot and Y. Bengio · 2010
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Nonlinear mixtures
C. Jutten, M. Babaie-Zadeh, and J. Karhunen · 2010
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Learning temporal coherent features through life-time sparsity
J. T. Springenberg and M. Riedmiller · 2012
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Likelihood-free inference via classification
M. U. Gutmann, R. Dutta, S. Kaski, and J. Corander · 2014
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Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2014
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An extension of slow feature analysis for nonlinear blind source separation
H. Sprekeler, T. Zito, and L. Wiskott · 2014
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P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.-A. Manzagol · 2010
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Investigating the electrophysiological basis of resting state networks using magnetoencephalography
M. J. Brookes et al · 2011
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A cortical core for dynamic integration of functional networks in the resting human brain
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Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics
M. U. Gutmann and A. Hyvärinen · 2012
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Characterization of neuromagnetic brain rhythms over time scales of minutes using spatial independent component analysis
P. Ramkumar, L. Parkkonen, R. Hari, and A. Hyvärinen · 2012
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N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 2014
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NICE: Non-linear independent components estimation
L. Dinh, D. Krueger, and Y. Bengio · 2015
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Unsupervised feature learning from temporal data
R. Goroshin, J. Bruna, J. Tompson, D. Eigen, and Y. LeCun · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
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From neural PCA to deep unsupervised learning
H. Valpola · 2015
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