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Patrik Hoyer

Affiliations: 
Helsinki Institute for Information Technology, Espoo, Finland 
Area:
Computation & Theory
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"Patrik Hoyer"
Mean distance: 14.78 (cluster 29)
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Parents

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Aapo Hyvärinen post-doc 2004- Helsinki Institute for Information Technology
Eero P. Simoncelli post-doc 2003-2003 NYU

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Publications

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Shimizu S, Hoyer PO, Hyvärinen A. (2009) Estimation of linear non-Gaussian acyclic models for latent factors Neurocomputing. 72: 2024-2027
Asunción Vicente M, Hoyer PO, Hyvärinen A. (2007) Equivalence of some common linear feature extraction techniques for appearance-based object recognition tasks. Ieee Transactions On Pattern Analysis and Machine Intelligence. 29: 896-900
Shimizu S, Hyvärinen A, Hoyer PO, et al. (2006) Finding a causal ordering via independent component analysis Computational Statistics and Data Analysis. 50: 3278-3293
Hoyer PO, Shimizu S, Hyvärinen A, et al. (2006) New permutation algorithms for causal discovery using ICA Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3889: 115-122
Shimizu S, Hyvärinen A, Kano Y, et al. (2006) Testing significance of mixing and demixing coefficients in ICA Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3889: 901-908
Hyvärinen A, Gutmann M, Hoyer PO. (2005) Statistical model of natural stimuli predicts edge-like pooling of spatial frequency channels in V2. Bmc Neuroscience. 6: 12
Hoyer PO, Hyvärinen A. (2002) A multi-layer sparse coding network learns contour coding from natural images. Vision Research. 42: 1593-605
Hoyer PO, Hyvärinen A. (2002) Sparse coding natural contours Neurocomputing. 44: 459-466
Hyvärinen A, Hoyer PO. (2001) A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images. Vision Research. 41: 2413-23
Hyvärinen A, Hoyer PO, Inki M. (2001) Topographic independent component analysis. Neural Computation. 13: 1527-58
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