- Learning Highlevel Independent Components of Images through a Spectral Representation
- Independent Component Analysis for NonNormal Factor Analysis
- Natural Language Engineering 16 (3): 277308. c Cambridge University Press 2010 doi:10.1017/S1351324910000057
- TPAMI-0656-1105.R2 0 "Equivalence of some common linear feature
- Blind separation of sources that have spatiotemporal variance dependencies
- A fast xedpoint algorithm for independent component analysis of complex valued signals
- Independent Component Analysis by General Nonlinear Hebbianlike Learning Rules
- Sparse Code Shrinkage: Denoising of Nongaussian Data by Maximum Likelihood Estimation
- Journal of Machine Learning Research 7 (2006) 2003-2030 Submitted 3/06; Revised 7/06; Published 10/06 A Linear Non-Gaussian Acyclic Model for Causal Discovery
- Image Denoising by Sparse Code Shrinkage Aapo Hyv#rinen, Patrik Hoyer and Erkki Oja
- Modelling image complexity by independent component analysis, with application to
- Behavioural priors: Learning to search efficiently in action planning
- Publication list Aapo Hyvarinen
- Estimating overcomplete independent component bases for image Aapo Hyvarinen and Mika Inki
- Independent component analysis of nondeterministic fMRI signal sources
- Fast and Robust Fixed-Point Algorithms for Independent Component Analysis
- A unifying model for blind separation of independent sources Aapo Hyvarinen
- Independent Component Analysis: Algorithms and Applications
- SimpleCellLike Receptive Fields Maximize Temporal Coherence in Natural Video
- Independent component analysis of short-time Fourier transforms for
- A multilayer sparse coding network learns contour coding from natural images #
- Computational Statistics & Data Analysis 51 (2007) 24992512 www.elsevier.com/locate/csda
- FAST ICA FOR NOISY DATA USING GAUSSIAN MOMENTS Aapo Hyv#rinen
- Consistency of pseudolikelihood estimation of fully visible Boltzmann machines
- Blind source separation by nonstationarity of variance: A cumulant-based approach
- Vision Research 41 (2001) 24132423 A two-layer sparse coding model learns simple and complex cell
- Causal discovery of linear acyclic models with arbitrary distributions Patrik O. Hoyer
- A unifying model for blind separation of independent sources Aapo Hyvarinen
- Independent Component Analysis for Timedependent Stochastic Processes
- Discovery of Exogenous Variables in Data with More Variables than Observations
- Optimal approximation of signal priors Aapo Hyvarinen #
- Independent Component Analysis in the Presence of Gaussian Noise by Maximizing Joint Likelihood
- An alternative approach to infomax and independent component analysis
- !!"$#&%' (%0)12435 !62#47!81!&9 !@A26 B!"C%'EDF#
- Connections between score matching, contrastive divergence, and pseudolikelihood for continuousvalued variables
- LETTER Communicated by Bartlett Mel Emergence of Phase-and Shift-Invariant Features by
- Brief communication Collinear context (and learning) change the profile
- Learning High-level Independent Components of Images through a Spectral Representation
- Independent Component Analysis: Algorithms and Applications
- Temporal Coherence, Natural Image Sequences, and the Visual Cortex
- FastISA: A fast fixedpoint algorithm for Independent Subspace Analysis
- INDEPENDENT COMPONENT ANALYSIS FOR BINARY DATA: AN EXPERIMENTAL STUDY
- A multi-layer sparse coding network learns contour coding from natural images
- Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces
- Topographic Independent Component Analysis Aapo Hyv#rinen, Patrik O. Hoyer, and Mika Inki
- Temporal Coherence, Natural Image Sequences, and the Visual Cortex
- Estimation of linear non-Gaussian acyclic models for latent factors
- Connection between multilayer perceptrons and regression using independent component analysis
- ESTIMATION THEORY AND INFORMATION GEOMETRY BASED ON DENOISING Aapo Hyvarinen
- IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 12, NO. 6, NOVEMBER 2001 1471 Blind Source Separation by Nonstationarity of Variance
- Testing significance of mixing and demixing coefficients in ICA
- A twolayer sparse coding model learns simple and complex cell receptive fields and topography from natural images
- Complexity pursuit: Separating interesting components from timeseries
- On the learning of nonlinear visual features from natural images by optimizing response energies
- Behavioral/Systems/Cognitive Representation of Cross-Frequency Spatial Phase
- Unsupervised learning of an embodied representation for action selection
- Blind separation of sources that have spatiotemporal variance dependencies
- Connections between score matching, contrastive divergence, and pseudolikelihood for continuous-valued variables
- Visual Features Underlying Perceived Brightness as Revealed by Classification Images
- ONEUNIT CONTRAST FUNCTIONS FOR INDEPENDENT COMPONENT ANALYSIS
- Imposing sparsity on the mixing matrix in independent component analysis
- New Approximations of Dioeerential Entropy for Independent Component Analysis
- Testing the ICA mixing matrix based on inter-subject or inter-session consistency
- Journal of Machine Learning Research 11 (2010) 1709-1731 Submitted 1/10; Published 5/10 Estimation of a Structural Vector Autoregression Model
- JMLR: Workshop and Conference Proceedings 13: 1-16 2nd Asian Conference on Machine Learning (ACML2010), Tokyo, Japan, Nov. 810, 2010.
- Journal of Machine Learning Research 12 (2011) 1225-1248 Submitted 1/11; Published 4/11 DirectLiNGAM: A Direct Method for Learning a Linear
- Discovery of linear non-gaussian acyclic models in the presence of latent classes
- Finding a causal ordering via independent component analysis
- On the Identifiability of the Post-Nonlinear Causal Model Dept. of Computer Science and HIIT
- Journal of Machine Learning Research 6 (2005) 695709 Submitted 11/04; Revised 3/05; Published 4/05 Estimation of Non-Normalized Statistical Models
- Estimating Markov Random Field Potentials for Natural Images
- A Two-Layer Model of Natural Stimuli Estimated with Score Matching
- Statistical Models of Natural Images and Cortical Visual Representation
- Independent Component Analysis Applied to Feature Extraction from Colour and Stereo Images
- Complex Cell Pooling and the Statistics of Natural Images Aapo Hyvarinen, Urs Koster
- Simple-Cell-Like Receptive Fields Maximize Temporal Coherence in Natural Video
- PROOF COPY [A-8652] 002307JOA [A-8652]002307JOA
- Emergence of conjunctive visual features by quadratic independent component analysis
- New Approximations of Di erential Entropy for Independent Component Analysis
- FastISA: A fast fixed-point algorithm for Independent Subspace Analysis
- Validating the independent components of neuroimaging time-series via clustering and
- A quasi-stochastic gradient algorithm for variance-dependent component analysis
- Learning encoding and decoding filters for data representation with a spiking neuron
- Learning to Segment Any Random Vector Aapo Hyvarinen and Jukka Perkio
- Consistency of pseudolikelihood estimation of fully visible Boltzmann machines
- New Approximations of Dioeerential Entropy for Independent Component
- Nonlinear Blind Source Separation by SelfOrganizing Maps Petteri Pajunen, Aapo Hyv#rinen, and Juha Karhunen
- The FixedPoint Algorithm and Maximum Likelihood Estimation for Independent
- Fast and Robust FixedPoint Algorithms for Independent Component Analysis
- Topographic Independent Component Analysis Aapo Hyvrinen, Patrik O. Hoyer, and Mika Inki
- Neurocomputing 50 (2003) 211222 www.elsevier.com/locate/neucom
- A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model
- Independent Component Analysis for Non-Normal Factor Analysis
- PROOF COPY [A8652] 002307JOA Bubbles: unifying framework for lowlevel
- Nonlinear Independent Component Analysis: Existence and Uniqueness Results
- Independent Component Analysis Applied to Feature Extraction from Colour and Stereo Images
- A Fast FixedPoint Algorithm for Independent Component Analysis
- Emergence of Topography and Complex Cell Properties from Natural Images
- Temporal and spatiotemporal coherence in simple-cell responses: A generative model of
- Independent component analysis of fMRI group studies by self-organizing clustering
- Gaussian Moments for Noisy Independent Component Analysis
- Survey on Independent Component Analysis Aapo Hyv#rinen
- Optimal approximation of signal priors Aapo Hyvarinen
- Source Separation and Higher-Order Causal Analysis of MEG and EEG
- Estimating Exogenous Variables in Data with More Variables than Observations
- Hermite Polynomials and Measures of Non-gaussianity
- r Human Brain Mapping 000:000000 (2011) r Characterization of Neuromagnetic Brain Rhythms
- Extracting Coactivated Features from Multiple Data Sets
- JMLR: Workshop and Conference Proceedings 1: xxx-xxx ACML2011 A general linear non-Gaussian state-space model
- Complex-Valued Independent Component Analysis of Natural Images
- Journal of Machine Learning Research 13 (2012) 307-361 Submitted 12/10; Revised 11/11; Published 2/12 Noise-Contrastive Estimation of Unnormalized Statistical Models,
- Learning Topographic Representations for Linearly Correlated Components
