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Hyvärinen, Aapo. Library of Congress/NACO National Library of the Netherlands National Diet Library, Japan NII (Japan) National Library of France German National Library NUKAT Center of Warsaw University Library ISNI BIBSYS National Library of Israel Sudoc [ABES], France

Aapo Hyvärinen Wikidata

VIAF ID: 49454194 (Personal)

Permalink: http://viaf.org/viaf/49454194

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Title Sources
Apprentissage de représentations en imagerie fonctionnelle Sudoc [ABES], France
Bubbles: a unifying framework for low-level statistical properties of natural image sequences. Wikidata
Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis Wikidata
Clustering via Mode Seeking by Direct Estimation of the Gradient of a Log-Density Wikidata
Collinear context (and learning) change the profile of the perceptual filter Wikidata
Connections between score matching, contrastive divergence, and pseudolikelihood for continuous-valued variables. Wikidata
Consistency of pseudolikelihood estimation of fully visible Boltzmann machines. Wikidata
Correlated topographic analysis: estimating an ordering of correlated components Wikidata
Decoding magnetoencephalographic rhythmic activity using spectrospatial information Wikidata
Equivalence of some common linear feature extraction techniques for appearance-based object recognition tasks. Wikidata
Estimating exogenous variables in data with more variables than observations. Wikidata
Estimation of linear non-Gaussian acyclic models for latent factors Wikidata
Extracting Coactivated Features from Multiple Data Sets Wikidata
Group-PCA for very large fMRI datasets. Wikidata
Independent component analysis Library of Congress/NACO National Library of the Netherlands Wikidata National Library of France German National Library NUKAT Center of Warsaw University Library BIBSYS National Library of Israel Sudoc [ABES], France
Learning Natural Image Structure with a Horizontal Product Model Wikidata
Learning representations from functional MRI data. Sudoc [ABES], France
Learning spike-timings based representations of sensory stimuli with leaky integrate-and-fire neurons Wikidata
Learning to Segment Any Random Vector Wikidata
Learning Visual Spatial Pooling by Strong PCA Dimension Reduction. Wikidata
A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing. Wikidata
A multi-layer sparse coding network learns contour coding from natural images. Wikidata
n2001005534 National Diet Library, Japan
Natural image statistics : a probabilistic approach to early computational vision Library of Congress/NACO Sudoc [ABES], France
Natural image statistics: Energy-based models estimated by score matching Wikidata
Noise-contrastive estimation: A new estimation principle for unnormalized statistical models Wikidata
Non-linear canonical correlation for joint analysis of MEG signals from two subjects Wikidata
Orthogonal Connectivity Factorization: Interpretable Decomposition of Variability in Correlation Matrices. Wikidata
ParceLiNGAM: a causal ordering method robust against latent confounders. Wikidata
Representation of cross-frequency spatial phase relationships in human visual cortex. Wikidata
Shokai dokuritsu seibun bunseki : Shingo kaiseki no atarashii sekai. National Diet Library, Japan
Simultaneous Estimation of Nongaussian Components and Their Correlation Structure. Wikidata
Some extensions of score matching Wikidata
Sparse and low-rank matrix regularization for learning time-varying Markov networks Wikidata
Spatial dependencies between local luminance and contrast in natural images Wikidata
Spatial frequency tuning in human retinotopic visual areas Wikidata
Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images Wikidata
Statistical model of natural stimuli predicts edge-like pooling of spatial frequency channels in V2 Wikidata
Statistical models of natural images and cortical visual representation. Wikidata
Template optimization and transfer in perceptual learning. Wikidata
Temporal and spatiotemporal coherence in simple-cell responses: a generative model of natural image sequences. Wikidata
Testing the ICA mixing matrix based on inter-subject or inter-session consistency. Wikidata
Three-way analysis of spectrospatial electromyography data: classification and interpretation Wikidata
Unifying Blind Separation and Clustering for Resting-State EEG/MEG Functional Connectivity Analysis. Wikidata
A unifying model for blind separation of independent sources Wikidata
Visual features underlying perceived brightness as revealed by classification images. Wikidata
詳解独立成分分析 : 信号解析の新しい世界 National Diet Library, Japan NII (Japan)

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