Patrik Hoyer
Patrik Hoyer
Alumni, Aalto University and University of Helsinki
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Cited by
Cited by
Non-negative matrix factorization with sparseness constraints.
PO Hoyer
Journal of machine learning research 5 (9), 2004
A linear non-Gaussian acyclic model for causal discovery.
S Shimizu, PO Hoyer, A Hyvärinen, A Kerminen, M Jordan
Journal of Machine Learning Research 7 (10), 2006
Non-negative sparse coding
PO Hoyer
Proceedings of the 12th IEEE workshop on neural networks for signal …, 2002
Nonlinear causal discovery with additive noise models
P Hoyer, D Janzing, JM Mooij, J Peters, B Schölkopf
Advances in neural information processing systems 21, 2008
Natural image statistics: A probabilistic approach to early computational vision.
A Hyvärinen, J Hurri, PO Hoyer
Springer Science & Business Media, 2009
Emergence of phase-and shift-invariant features by decomposition of natural images into independent feature subspaces
A Hyvärinen, P Hoyer
Neural computation 12 (7), 1705-1720, 2000
Topographic independent component analysis
A Hyvärinen, PO Hoyer, M Inki
Neural computation 13 (7), 1527-1558, 2001
Sparse code shrinkage: Denoising by nonlinear maximum likelihood estimation
A Hyvärinen, P Hoyer, E Oja
Advances in Neural Information Processing Systems 11, 1998
DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model
S Shimizu, T Inazumi, Y Sogawa, A Hyvarinen, Y Kawahara, T Washio, ...
Journal of Machine Learning Research-JMLR 12 (Apr), 1225-1248, 2011
Estimation of a structural vector autoregression model using non-gaussianity.
A Hyvärinen, K Zhang, S Shimizu, PO Hoyer
Journal of Machine Learning Research 11 (5), 2010
Independent component analysis applied to feature extraction from colour and stereo images
PO Hoyer, A Hyvärinen
Network: computation in neural systems 11 (3), 191-210, 2000
A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images
A Hyvärinen, PO Hoyer
Vision research 41 (18), 2413-2423, 2001
Estimation of causal effects using linear non-Gaussian causal models with hidden variables
PO Hoyer, S Shimizu, AJ Kerminen, M Palviainen
International Journal of Approximate Reasoning 49 (2), 362-378, 2008
Interpreting neural response variability as Monte Carlo sampling of the posterior
P Hoyer, A Hyvärinen
Advances in neural information processing systems 15, 2002
Causal inference by independent component analysis: Theory and applications
A Moneta, D Entner, PO Hoyer, A Coad
Oxford Bulletin of Economics and Statistics 75 (5), 705-730, 2013
A multi-layer sparse coding network learns contour coding from natural images
PO Hoyer, A Hyvärinen
Vision research 42 (12), 1593-1605, 2002
Discovering cyclic causal models by independent components analysis
G Lacerda, PL Spirtes, J Ramsey, PO Hoyer
arXiv preprint arXiv:1206.3273, 2012
Image denoising by sparse code shrinkage
S Haykin, B Kosko
Wiley-IEEE Press, 2001
Modeling receptive fields with non-negative sparse coding
PO Hoyer
Neurocomputing 52, 547-552, 2003
On causal discovery from time series data using FCI
D Entner, PO Hoyer
Probabilistic graphical models, 121-128, 2010
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