Image feature extraction by sparse coding and independent component analysis. - Aapo Hyvärinen; Erkki Oja; Patrik O. Hoyer; Jarmo Hurri (ICPR, 1998)

Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation. - Aapo Hyvärinen; Patrik O. Hoyer; Erkki Oja (NIPS, 1998)

Estimating signal-adapted wavelets using sparseness criteria. - Patrik O. Hoyer; Aapo Hyvärinen (IJCNN, 1999)

Independent subspace analysis shows emergence of phase and shift invariant features from natural images. - Aapo Hyvärinen; Patrik O. Hoyer (IJCNN, 1999)

Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA. - Aapo Hyvärinen; Patrik O. Hoyer (NIPS, 1999)

Image Feature Extraction and Denoising by Sparse Coding. - Erkki Oja; Aapo Hyvärinen; Patrik O. Hoyer (Pattern Anal. Appl., 1999)

Topographic ICA as a Model of Natural Image Statistics. - Aapo Hyvärinen; Patrik O. Hoyer; Mika Inki (Biologically Motivated Computer Vision, 2000)

Feature Extraction from Color and Stereo Images Using ICA. - Patrik O. Hoyer; Aapo Hyvärinen (IJCNN (3), 2000)

Topographic ICA as a Model of V1 Receptive Fields. - Aapo Hyvärinen; Patrik O. Hoyer; Mika Inki (IJCNN (4), 2000)

Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces. - Aapo Hyvärinen; Patrik O. Hoyer (Neural Comput., 2000)

A new approach to uncover dynamic phase coordination and synchronization. - Dirk Hoyer; Patrik O. Hoyer; Ulrich Zwiener (IEEE Trans. Biomed. Eng., 2000)

Topographic independent component analysis as a model of V1 organization and receptive fields. - Aapo Hyvärinen; Patrik O. Hoyer (Neurocomputing, 2001)

Topographic Independent Component Analysis. - Aapo Hyvärinen; Patrik O. Hoyer; Mika Inki (Neural Comput., 2001)

Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior. - Patrik O. Hoyer; Aapo Hyvärinen (NIPS, 2002)

Non-negative sparse coding. - Patrik O. Hoyer (NNSP, 2002)

Sparse coding of natural contours. - Patrik O. Hoyer; Aapo Hyvärinen (Neurocomputing, 2002)

Probabilistic models of early vision. - Patrik O. Hoyer (2002)

Modeling receptive fields with non-negative sparse coding. - Patrik O. Hoyer (Neurocomputing, 2003)

Non-negative Matrix Factorization with Sparseness Constraints. - Patrik O. Hoyer (J. Mach. Learn. Res., 2004)

Discovery of Non-gaussian Linear Causal Models using ICA. - Shohei Shimizu; Aapo Hyvärinen; Yutaka Kano; Patrik O. Hoyer (UAI, 2005)

New Permutation Algorithms for Causal Discovery Using ICA. - Patrik O. Hoyer; Shohei Shimizu; Aapo Hyvärinen; Yutaka Kano; Antti J. Kerminen (ICA, 2006)

Testing Significance of Mixing and Demixing Coefficients in ICA. - Shohei Shimizu; Aapo Hyvärinen; Yutaka Kano; Patrik O. Hoyer; Antti J. Kerminen (ICA, 2006)

Estimation of linear, non-gaussian causal models in the presence of confounding latent variables. - Patrik O. Hoyer; Shohei Shimizu; Antti J. Kerminen (Probabilistic Graphical Models, 2006)

Finding a causal ordering via independent component analysis. - Shohei Shimizu; Aapo Hyvärinen; Patrik O. Hoyer; Yutaka Kano (Comput. Stat. Data Anal., 2006)

A Linear Non-Gaussian Acyclic Model for Causal Discovery. - Shohei Shimizu; Patrik O. Hoyer; Aapo Hyvärinen; Antti J. Kerminen (J. Mach. Learn. Res., 2006)

Equivalence of Some Common Linear Feature Extraction Techniques for Appearance-Based Object Recognition Tasks. - Maria Asunción Vicente; Patrik O. Hoyer; Aapo Hyvärinen (IEEE Trans. Pattern Anal. Mach. Intell., 2007)

Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity. - Aapo Hyvärinen; Shohei Shimizu; Patrik O. Hoyer (ICML, 2008)

Nonlinear causal discovery with additive noise models. - Patrik O. Hoyer; Dominik Janzing; Joris M. Mooij; Jonas Peters; Bernhard Schölkopf (NIPS, 2008)

Causal discovery of linear acyclic models with arbitrary distributions. - Patrik O. Hoyer; Aapo Hyvärinen; Richard Scheines; Peter Spirtes; Joseph D. Ramsey; Gustavo Lacerda; Shohei Shimizu (UAI, 2008)

Discovering Cyclic Causal Models by Independent Components Analysis. - Gustavo Lacerda; Peter Spirtes; Joseph D. Ramsey; Patrik O. Hoyer (UAI, 2008)

Estimation of causal effects using linear non-Gaussian causal models with hidden variables. - Patrik O. Hoyer; Shohei Shimizu; Antti J. Kerminen; Markus Palviainen (Int. J. Approx. Reason., 2008)

Bayesian Discovery of Linear Acyclic Causal Models. - Patrik O. Hoyer; Antti Hyttinen (UAI, 2009)

Estimation of linear non-Gaussian acyclic models for latent factors. - Shohei Shimizu; Patrik O. Hoyer; Aapo Hyvärinen (Neurocomputing, 2009)

Natural Image Statistics - A Probabilistic Approach to Early Computational Vision - Aapo Hyvärinen; Jarmo Hurri; Patrik O. Hoyer (Springer, 2009)

Telling cause from effect based on high-dimensional observations. - Dominik Janzing; Patrik O. Hoyer; Bernhard Schölkopf (ICML, 2010)

Discovering Unconfounded Causal Relationships Using Linear Non-Gaussian Models. - Doris Entner; Patrik O. Hoyer (JSAI-isAI Workshops, 2010)

Combining Experiments to Discover Linear Cyclic Models with Latent Variables. - Frederick Eberhardt; Patrik O. Hoyer; Richard Scheines (AISTATS, 2010)

Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity. - Aapo Hyvärinen; Kun Zhang 001; Shohei Shimizu; Patrik O. Hoyer (J. Mach. Learn. Res., 2010)

Noisy-OR Models with Latent Confounding. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (UAI, 2011)

Causal Search in Structural Vector Autoregressive Models. - Alessio Moneta; Nadine Chlass; Doris Entner; Patrik O. Hoyer (NIPS Mini-Symposium on Causality in Time Series, 2011)

DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model. - Shohei Shimizu; Takanori Inazumi; Yasuhiro Sogawa; Aapo Hyvärinen; Yoshinobu Kawahara; Takashi Washio; Patrik O. Hoyer; Kenneth Bollen (J. Mach. Learn. Res., 2011)

Estimating a Causal Order among Groups of Variables in Linear Models. - Doris Entner; Patrik O. Hoyer (ICANN (2), 2012)

Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (UAI, 2012)

Statistical test for consistent estimation of causal effects in linear non-Gaussian models. - Doris Entner; Patrik O. Hoyer; Peter Spirtes (AISTATS, 2012)

Learning linear cyclic causal models with latent variables. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (J. Mach. Learn. Res., 2012)

Data-driven covariate selection for nonparametric estimation of causal effects. - Doris Entner; Patrik O. Hoyer; Peter Spirtes (AISTATS, 2013)

Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure. - Antti Hyttinen; Patrik O. Hoyer; Frederick Eberhardt; Matti Järvisalo (UAI, 2013)

Experiment selection for causal discovery. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (J. Mach. Learn. Res., 2013)