P185
P1855
Statistical model of natural stimuli predicts edge-like pooling of spatial frequency channels in V2Group-level spatial independent component analysis of Fourier envelopes of resting-state MEG data.Fast and robust fixed-point algorithms for independent component analysisVisual features underlying perceived brightness as revealed by classification images.Estimating exogenous variables in data with more variables than observations.Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural imagesThree-way analysis of spectrospatial electromyography data: classification and interpretationCharacterizing Variability of Modular Brain Connectivity with Constrained Principal Component AnalysisNon-linear canonical correlation for joint analysis of MEG signals from two subjectsSimultaneous Estimation of Nongaussian Components and Their Correlation Structure.Orthogonal Connectivity Factorization: Interpretable Decomposition of Variability in Correlation Matrices.A Hierarchical Statistical Model of Natural Images Explains Tuning Properties in V2.Unifying Blind Separation and Clustering for Resting-State EEG/MEG Functional Connectivity Analysis.A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing.Independent component analysis: recent advances.Group-PCA for very large fMRI datasets.Testing independent component patterns by inter-subject or inter-session consistency.A two-layer model of natural stimuli estimated with score matching.Decoding emotional valence from electroencephalographic rhythmic activity.Noise-contrastive estimation: A new estimation principle for unnormalized statistical modelsTemporal and spatiotemporal coherence in simple-cell responses: a generative model of natural image sequences.Independent component analysis of nondeterministic fMRI signal sources.Statistical models of natural images and cortical visual representation.Simple-cell-like receptive fields maximize temporal coherence in natural video.Simultaneous blind separation and clustering of coactivated EEG/MEG sources for analyzing spontaneous brain activity.Representation of cross-frequency spatial phase relationships in human visual cortex.Independent component analysis of short-time Fourier transforms for spontaneous EEG/MEG analysis.A multi-layer sparse coding network learns contour coding from natural images.A Bayesian inverse solution using independent component analysis.Characterization of neuromagnetic brain rhythms over time scales of minutes using spatial independent component analysis.ParceLiNGAM: a causal ordering method robust against latent confounders.Template optimization and transfer in perceptual learning.Testing the ICA mixing matrix based on inter-subject or inter-session consistency.Learning Visual Spatial Pooling by Strong PCA Dimension Reduction.A three-layer model of natural image statistics.Equivalence of some common linear feature extraction techniques for appearance-based object recognition tasks.Connections between score matching, contrastive divergence, and pseudolikelihood for continuous-valued variables.Consistency of pseudolikelihood estimation of fully visible Boltzmann machines.Complex cell pooling and the statistics of natural images.Validating the independent components of neuroimaging time series via clustering and visualization.
P50
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P50
description
Finnish professor of computer ...... i; University College London)
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Fins informaticus
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finnischer Informatiker und Informatiker
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finsk maskinlæringsforsker
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informáticu teóricu finlandés
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suomalainen tietojenkäsittelyt ...... to, University College London)
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عالِم حاسوب فنلندي
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