Patrik O. Hoyer

59 papers A* 2A 10B 3Journal 28Unranked 14

Year	Rank	Type	Title / Venue / Authors
2013	A	`conf`	Data-driven covariate selection for nonparametric estimation of causal effects. AISTATS Doris Entner, Patrik O. Hoyer, Peter Spirtes
2013	A	`conf`	Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure. UAI Antti Hyttinen, Patrik O. Hoyer, Frederick Eberhardt, Matti Järvisalo
2013	J	`jnl`	Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure. CoRR Antti Hyttinen, Patrik O. Hoyer, Frederick Eberhardt, Matti Järvisalo
2013	J	`jnl`	Experiment selection for causal discovery. J. Mach. Learn. Res. Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2012	J	`jnl`	Bayesian Discovery of Linear Acyclic Causal Models CoRR Patrik O. Hoyer, Antti Hyttinen
2012	J	`jnl`	Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables CoRR Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2012	A	`conf`	Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables. UAI Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2012	J	`jnl`	Causal discovery of linear acyclic models with arbitrary distributions CoRR Patrik O. Hoyer, Aapo Hyvärinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu
2012	J	`jnl`	Discovering Cyclic Causal Models by Independent Components Analysis CoRR Gustavo Lacerda, Peter Spirtes, Joseph D. Ramsey, Patrik O. Hoyer
2012	J	`jnl`	Discovery of non-gaussian linear causal models using ICA CoRR Shohei Shimizu, Aapo Hyvärinen, Yutaka Kano, Patrik O. Hoyer
2012	J	`jnl`	Estimating a Causal Order among Groups of Variables in Linear Models CoRR Doris Entner, Patrik O. Hoyer
2012	—	`conf`	Estimating a Causal Order among Groups of Variables in Linear Models. ICANN (2) Doris Entner, Patrik O. Hoyer
2012	J	`jnl`	Learning linear cyclic causal models with latent variables. J. Mach. Learn. Res. Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2012	J	`jnl`	Noisy-OR Models with Latent Confounding CoRR Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2012	A	`conf`	Statistical test for consistent estimation of causal effects in linear non-Gaussian models. AISTATS Doris Entner, Patrik O. Hoyer, Peter Spirtes
2011	—	`conf`	Causal Search in Structural Vector Autoregressive Models. NIPS Mini-Symposium on Causality in Time Series Alessio Moneta, Nadine Chlass, Doris Entner, Patrik O. Hoyer
2011	J	`jnl`	DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model. J. Mach. Learn. Res. Shohei Shimizu, Takanori Inazumi, Yasuhiro Sogawa, Aapo Hyvärinen, Yoshinobu Kawahara, Takashi Washio, Patrik O. Hoyer, Kenneth Bollen
2011	A	`conf`	Noisy-OR Models with Latent Confounding. UAI Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
2010	A	`conf`	Combining Experiments to Discover Linear Cyclic Models with Latent Variables. AISTATS Frederick Eberhardt, Patrik O. Hoyer, Richard Scheines
2010	—	`conf`	Discovering Unconfounded Causal Relationships Using Linear Non-Gaussian Models. JSAI-isAI Workshops Doris Entner, Patrik O. Hoyer
2010	J	`jnl`	Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity. J. Mach. Learn. Res. Aapo Hyvärinen, Kun Zhang, Shohei Shimizu, Patrik O. Hoyer
2010	A*	`conf`	Telling cause from effect based on high-dimensional observations. ICML Dominik Janzing, Patrik O. Hoyer, Bernhard Schölkopf
2009	A	`conf`	Bayesian Discovery of Linear Acyclic Causal Models. UAI Patrik O. Hoyer, Antti Hyttinen
2009	J	`jnl`	Estimation of linear non-Gaussian acyclic models for latent factors. Neurocomputing Shohei Shimizu, Patrik O. Hoyer, Aapo Hyvärinen
2009	—	`book`	Natural Image Statistics - A Probabilistic Approach to Early Computational Vision Aapo Hyvärinen, Jarmo Hurri, Patrik O. Hoyer
2008	A	`conf`	Causal discovery of linear acyclic models with arbitrary distributions. UAI Patrik O. Hoyer, Aapo Hyvärinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu
2008	A*	`conf`	Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity. ICML Aapo Hyvärinen, Shohei Shimizu, Patrik O. Hoyer
2008	A	`conf`	Discovering Cyclic Causal Models by Independent Components Analysis. UAI Gustavo Lacerda, Peter Spirtes, Joseph D. Ramsey, Patrik O. Hoyer
2008	J	`jnl`	Estimation of causal effects using linear non-Gaussian causal models with hidden variables. Int. J. Approx. Reason. Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen, Markus Palviainen
2008	—	`conf`	Nonlinear causal discovery with additive noise models. NIPS Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, Bernhard Schölkopf
2007	J	`jnl`	Equivalence of Some Common Linear Feature Extraction Techniques for Appearance-Based Object Recognition Tasks. IEEE Trans. Pattern Anal. Mach. Intell. Maria Asunción Vicente, Patrik O. Hoyer, Aapo Hyvärinen
2006	J	`jnl`	A Linear Non-Gaussian Acyclic Model for Causal Discovery. J. Mach. Learn. Res. Shohei Shimizu, Patrik O. Hoyer, Aapo Hyvärinen, Antti J. Kerminen
2006	J	`jnl`	Estimation of linear, non-gaussian causal models in the presence of confounding latent variables CoRR Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen
2006	—	`conf`	Estimation of linear, non-gaussian causal models in the presence of confounding latent variables. Probabilistic Graphical Models Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen
2006	J	`jnl`	Finding a causal ordering via independent component analysis. Comput. Stat. Data Anal. Shohei Shimizu, Aapo Hyvärinen, Patrik O. Hoyer, Yutaka Kano
2006	—	`conf`	New Permutation Algorithms for Causal Discovery Using ICA. ICA Patrik O. Hoyer, Shohei Shimizu, Aapo Hyvärinen, Yutaka Kano, Antti J. Kerminen
2006	—	`conf`	Testing Significance of Mixing and Demixing Coefficients in ICA. ICA Shohei Shimizu, Aapo Hyvärinen, Yutaka Kano, Patrik O. Hoyer, Antti J. Kerminen
2005	A	`conf`	Discovery of Non-gaussian Linear Causal Models using ICA. UAI Shohei Shimizu, Aapo Hyvärinen, Yutaka Kano, Patrik O. Hoyer
2004	J	`jnl`	Non-negative Matrix Factorization with Sparseness Constraints. J. Mach. Learn. Res. Patrik O. Hoyer
2004	J	`jnl`	Non-negative matrix factorization with sparseness constraints CoRR Patrik O. Hoyer
2003	J	`jnl`	Modeling receptive fields with non-negative sparse coding. Neurocomputing Patrik O. Hoyer
2002	—	`conf`	Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior. NIPS Patrik O. Hoyer, Aapo Hyvärinen
2002	J	`jnl`	Non-negative sparse coding CoRR Patrik O. Hoyer
2002	—	`conf`	Non-negative sparse coding. NNSP Patrik O. Hoyer
2002	—	`—`	Probabilistic models of early vision. Patrik O. Hoyer
2002	J	`jnl`	Sparse coding of natural contours. Neurocomputing Patrik O. Hoyer, Aapo Hyvärinen
2001	J	`jnl`	Topographic Independent Component Analysis. Neural Comput. Aapo Hyvärinen, Patrik O. Hoyer, Mika Inki
2001	J	`jnl`	Topographic independent component analysis as a model of V1 organization and receptive fields. Neurocomputing Aapo Hyvärinen, Patrik O. Hoyer
2000	J	`jnl`	A new approach to uncover dynamic phase coordination and synchronization. IEEE Trans. Biomed. Eng. Dirk Hoyer, Patrik O. Hoyer, Ulrich Zwiener
2000	J	`jnl`	Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces. Neural Comput. Aapo Hyvärinen, Patrik O. Hoyer
2000	—	`conf`	Feature Extraction from Color and Stereo Images Using ICA. IJCNN (3) Patrik O. Hoyer, Aapo Hyvärinen
2000	—	`conf`	Topographic ICA as a Model of Natural Image Statistics. Biologically Motivated Computer Vision Aapo Hyvärinen, Patrik O. Hoyer, Mika Inki
2000	—	`conf`	Topographic ICA as a Model of V1 Receptive Fields. IJCNN (4) Aapo Hyvärinen, Patrik O. Hoyer, Mika Inki
1999	—	`conf`	Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA. NIPS Aapo Hyvärinen, Patrik O. Hoyer
1999	B	`conf`	Estimating signal-adapted wavelets using sparseness criteria. IJCNN Patrik O. Hoyer, Aapo Hyvärinen
1999	J	`jnl`	Image Feature Extraction and Denoising by Sparse Coding. Pattern Anal. Appl. Erkki Oja, Aapo Hyvärinen, Patrik O. Hoyer
1999	B	`conf`	Independent subspace analysis shows emergence of phase and shift invariant features from natural images. IJCNN Aapo Hyvärinen, Patrik O. Hoyer
1998	B	`conf`	Image feature extraction by sparse coding and independent component analysis. ICPR Aapo Hyvärinen, Erkki Oja, Patrik O. Hoyer, Jarmo Hurri
1998	—	`conf`	Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation. NIPS Aapo Hyvärinen, Patrik O. Hoyer, Erkki Oja