# Aapo Hyvärinen

Finnish professor of computer science

## Aapo Hyvärinen's AcademicInfluence.com Rankings

## Download Badge

Computer Science

## Aapo Hyvärinen's Degrees

- PhD Computer Science University of Helsinki

## Similar Degrees You Can Earn

## Why Is Aapo Hyvärinen Influential?

(Suggest an Edit or Addition)According to Wikipedia, Aapo Johannes Hyvärinen is a Finnish professor of computer science at the University of Helsinki and known for his research in independent component analysis. Education and career Hyvärinen was born in Helsinki and studied mathematics at the University of Helsinki and received his Doctor of Technology in information science in 1997 at the Helsinki University of Technology under the supervision of Erkki Oja. His doctoral thesis is titled Independent component analysis: A neural network approach. Since then, Hyvärinen has conducted research especially in relation to the independent component analysis. In November 2007, he was appointed as a professor at the University of Helsinki. Hyvärinen has been a member of the Finnish Academy of Sciences since 2016. From August 2016 to March 2019, he held a professorship in machine learning at the Gatsby Computational Neuroscience Unit of the University College London.

## Aapo Hyvärinen's Published Works

### Published Works

- Independent component analysis: algorithms and applications (2000) (8083)
- Fast and robust fixed-point algorithms for independent component analysis (1999) (6058)
- Independent Component Analysis (2001) (4123)
- A Fast Fixed-Point Algorithm for Independent Component Analysis (1997) (1670)
- Noise-contrastive estimation: A new estimation principle for unnormalized statistical models (2010) (1575)
- Survey on Independent Component Analysis (1999) (1347)
- A Linear Non-Gaussian Acyclic Model for Causal Discovery (2006) (1129)
- Validating the independent components of neuroimaging time series via clustering and visualization (2004) (1125)
- Estimation of Non-Normalized Statistical Models by Score Matching (2005) (862)
- A Fast Fixed-Point Algorithm for Independent Component Analysis of Complex Valued Signals (2000) (808)
- Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics (2012) (664)
- Natural Image Statistics - A Probabilistic Approach to Early Computational Vision (2009) (640)
- Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces (2000) (619)
- Nonlinear independent component analysis: Existence and uniqueness results (1999) (572)
- Topographic Independent Component Analysis (2001) (521)
- New Approximations of Differential Entropy for Independent Component Analysis and Projection Pursuit (1997) (446)
- Sparse Code Shrinkage: Denoising of Nongaussian Data by Maximum Likelihood Estimation (1999) (431)
- On the Identifiability of the Post-Nonlinear Causal Model (2009) (405)
- Independent component analysis of nondeterministic fMRI signal sources (2003) (384)
- Independent component analysis of fMRI group studies by self-organizing clustering (2005) (357)
- DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model (2011) (327)
- Independent component analysis: recent advances (2013) (302)
- A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images (2001) (297)
- Variational Autoencoders and Nonlinear ICA: A Unifying Framework (2019) (297)
- Independent component analysis applied to feature extraction from colour and stereo images (2000) (283)
- Independent component analysis by general nonlinear Hebbian-like learning rules (1998) (280)
- The Fixed-Point Algorithm and Maximum Likelihood Estimation for Independent Component Analysis (1999) (270)
- Icasso: software for investigating the reliability of ICA estimates by clustering and visualization (2003) (252)
- Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity (2010) (250)
- Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA (2016) (246)
- Independent Component Analysis: A Tutorial (1999) (234)
- Gaussian moments for noisy independent component analysis (1999) (224)
- Some extensions of score matching (2007) (204)
- Group-PCA for very large fMRI datasets (2014) (201)
- A multi-layer sparse coding network learns contour coding from natural images (2002) (178)
- Pairwise likelihood ratios for estimation of non-Gaussian structural equation models (2013) (176)
- Independent component analysis in the presence of Gaussian noise by maximizing joint likelihood (1998) (175)
- Independent component analysis of short-time Fourier transforms for spontaneous EEG/MEG analysis (2010) (175)
- Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning (2018) (165)
- Complexity Pursuit: Separating Interesting Components from Time Series (2001) (164)
- Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior (2002) (163)
- Spatial frequency tuning in human retinotopic visual areas. (2008) (153)
- Nonlinear Blind Source Separation by Self-Organizing Maps (1996) (131)
- A family of fixed-point algorithms for independent component analysis (1997) (127)
- Nonlinear ICA of Temporally Dependent Stationary Sources (2017) (119)
- Simple-Cell-Like Receptive Fields Maximize Temporal Coherence in Natural Video (2003) (119)
- Learning Features by Contrasting Natural Images with Noise (2009) (115)
- Blind source separation by nonstationarity of variance: a cumulant-based approach (2001) (114)
- One-unit contrast functions for independent component analysis: a statistical analysis (1997) (113)
- Applications of neural blind separation to signal and image processing (1997) (112)
- Bubbles: a unifying framework for low-level statistical properties of natural image sequences. (2003) (110)
- Density Estimation in Infinite Dimensional Exponential Families (2013) (109)
- Learning Natural Image Structure with a Horizontal Product Model (2009) (108)
- Image feature extraction by sparse coding and independent component analysis (1998) (107)
- Consistency of Pseudolikelihood Estimation of Fully Visible Boltzmann Machines (2006) (98)
- Independent Component Analysis for Time-dependent Stochastic Processes (1998) (89)
- Uncovering the structure of clinical EEG signals with self-supervised learning (2020) (86)
- Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity (2008) (84)
- A fast algorithm for estimating overcomplete ICA bases for image windows (1999) (84)
- Sparse Code Shrinkage: Denoising by Nonlinear Maximum Likelihood Estimation (1998) (75)
- Fast ICA for noisy data using Gaussian moments (1999) (73)
- Distinguishing causes from effects using nonlinear acyclic causal models (2008) (68)
- Complex cell pooling and the statistics of natural images (2007) (67)
- Causal discovery of linear acyclic models with arbitrary distributions (2008) (67)
- FastISA: A fast fixed-point algorithm for independent subspace analysis (2006) (65)
- Image Feature Extraction Using Independent Component Analysis (1996) (64)
- Simple Neuron Models for Independent Component Analysis (1996) (64)
- One-unit Learning Rules for Independent Component Analysis (1996) (62)
- Connections Between Score Matching, Contrastive Divergence, and Pseudolikelihood for Continuous-Valued Variables (2007) (60)
- Deep Energy Estimator Networks (2018) (59)
- Estimating Overcomplete Independent Component Bases for Image Windows (2002) (55)
- Causal Discovery with General Non-Linear Relationships using Non-Linear ICA (2019) (55)
- Independent Component Analysis: Fast ICA by a fixed-point algorithm that maximizes non-Gaussianity (2001) (53)
- ICE-BeeM: Identifiable Conditional Energy-Based Deep Models (2020) (53)
- Testing the ICA mixing matrix based on inter-subject or inter-session consistency (2011) (52)
- Optimization Theory and Algorithms (2009) (51)
- Modelling Image Complexity by Independent Component Analysis, with Application to Content-Based Image Retrieval (2009) (49)
- Representation of Cross-Frequency Spatial Phase Relationships in Human Visual Cortex (2009) (48)
- Blind signal separation and independent component analysis (2002) (48)
- Equivalence of Some Common Linear Feature Extraction Techniques for Appearance-Based Object Recognition Tasks (2007) (47)
- Emergence of Topography and Complex Cell Properties from Natural Images using Extensions of ICA (1999) (47)
- A unifying model for blind separation of independent sources (2005) (45)
- Clustering via Mode Seeking by Direct Estimation of the Gradient of a Log-Density (2014) (45)
- Statistical model of natural stimuli predicts edge-like pooling of spatial frequency channels in V2 (2005) (45)
- ParceLiNGAM: A Causal Ordering Method Robust Against Latent Confounders (2013) (45)
- Discovery of Non-gaussian Linear Causal Models using ICA (2005) (44)
- A Two-Layer ICA-Like Model Estimated by Score Matching (2007) (43)
- Statistical Models of Natural Images and Cortical Visual Representation (2010) (43)
- Blind separation of sources that have spatiotemporal variance dependencies (2004) (42)
- Causal Autoregressive Flows (2020) (42)
- Estimation of linear non-Gaussian acyclic models for latent factors (2009) (40)
- Characterization of neuromagnetic brain rhythms over time scales of minutes using spatial independent component analysis (2012) (40)
- A Family of Computationally E cient and Simple Estimators for Unnormalized Statistical Models (2010) (39)
- Causality Discovery with Additive Disturbances: An Information-Theoretical Perspective (2009) (38)
- ICA of complex valued signals: a fast and robust deflationary algorithm (2000) (37)
- Neural Empirical Bayes (2019) (36)
- Imposing sparsity on the mixing matrix in independent component analysis (2002) (36)
- WordICA—emergence of linguistic representations for words by independent component analysis (2010) (35)
- A Two-Layer Model of Natural Stimuli Estimated with Score Matching (2010) (34)
- Self-Supervised Representation Learning from Electroencephalography Signals (2019) (33)
- Wavelets and Natural Image Statistics (2003) (32)
- A Hierarchical Statistical Model of Natural Images Explains Tuning Properties in V2 (2015) (28)
- Learning Visual Spatial Pooling by Strong PCA Dimension Reduction (2016) (28)
- Temporal and spatiotemporal coherence in simple-cell responses: a generative model of natural image sequences (2003) (27)
- ICA with Sparse Connections: Revisited (2009) (27)
- Estimating Markov Random Field Potentials for Natural Images (2009) (26)
- Topographic independent component analysis as a model of V1 organization and receptive fields (2001) (26)
- Image Feature Extraction and Denoising by Sparse Coding (1999) (26)
- Optimal Approximation of Signal Priors (2008) (25)
- Finding a causal ordering via independent component analysis (2006) (25)
- Spatio-Chromatic Adaptation via Higher-Order Canonical Correlation Analysis of Natural Images (2014) (25)
- Estimation of Non-normalized Statistical Models (2009) (24)
- A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model (2009) (24)
- Group-level spatial independent component analysis of Fourier envelopes of resting-state MEG data (2014) (23)
- Decoding magnetoencephalographic rhythmic activity using spectrospatial information (2013) (22)
- A three-layer model of natural image statistics (2013) (22)
- Testing Independent Component Patterns by Inter-Subject or Inter-Session Consistency (2013) (21)
- Pairwise Measures of Causal Direction in Linear Non-Gaussian Acyclic Models (2010) (21)
- Brain activity reflects the predictability of word sequences in listened continuous speech (2020) (20)
- Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA (2021) (20)
- Statistical models of images and early vision (2005) (20)
- Independent Component Analysis For Binary Data: An Experimental Study (2001) (19)
- Source Separation and Higher-Order Causal Analysis of MEG and EEG (2010) (18)
- A unified probabilistic model for learning latent factors and their connectivities from high-dimensional data (2018) (18)
- Neural Independent Component Analysis - Approaches and Applications (1998) (18)
- Emergence of Linguistic Features: Independent Component Analysis of Contexts (2005) (18)
- Estimating exogenous variables in data with more variables than observations (2011) (17)
- Temporal Coherence, Natural Image Sequences, and the Visual Cortex (2002) (17)
- Relative gradient optimization of the Jacobian term in unsupervised deep learning (2020) (17)
- Principal Component Analysis and Whitening (2002) (17)
- ICA by Maximization of Nongaussianity (2002) (16)
- Topographic ICA as a model of V1 receptive fields (2000) (16)
- Spatial dependencies between local luminance and contrast in natural images. (2008) (16)
- A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing (2016) (15)
- Visual Features Underlying Perceived Brightness as Revealed by Classification Images (2009) (14)
- Decoding attentional states for neurofeedback: Mindfulness vs. wandering thoughts (2019) (14)
- Principal Components and Whitening (2009) (14)
- A neuron that learns to separate one signal from a mixture of independent sources (1996) (14)
- A General Linear Non-Gaussian State-Space Model (2011) (14)
- Topographic ICA as a Model of Natural Image Statistics (2000) (13)
- Emergence of conjunctive visual features by quadratic independent component analysis (2006) (13)
- Testing Significance of Mixing and Demixing Coefficients in ICA (2006) (13)
- Estimation of unnormalized statistical models without numerical integration (2013) (12)
- Investigating shape perception by classification images. (2014) (12)
- Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS) (2010) (12)
- Connection between multilayer perceptrons and regression using independent component analysis (2003) (12)
- Nonlinear ICA of fMRI reveals primitive temporal structures linked to rest, task, and behavioral traits (2020) (12)
- Beyond independent components (1999) (12)
- Non-linear canonical correlation for joint analysis of MEG signals from two subjects (2013) (12)
- Three-Way Analysis of Spectrospatial Electromyography Data: Classification and Interpretation (2015) (12)
- Feature extraction from colour and stereo images using ICA (2000) (11)
- Learning high-level independent components of images through a spectral representation (2004) (11)
- An alternative approach to infomax and independent component analysis (2002) (10)
- Independent Component Analysis of Images (2014) (10)
- Independent subspace analysis shows emergence of phase and shift invariant features from natural images (1999) (9)
- Hermite Polynomials and Measures of Non-gaussianity (2011) (9)
- Collinear context (and learning) change the profile of the perceptual filter (2006) (9)
- Pattern Recognition (ICPR), 2012 21st International Conference on (2012) (9)
- Sparse coding of natural contours (2002) (9)
- Unifying Blind Separation and Clustering for Resting-State EEG/MEG Functional Connectivity Analysis (2015) (8)
- Extracting Coactivated Features from Multiple Data Sets (2011) (8)
- Independent Component Analysis for Non-Normal Factor Analysis (2003) (8)
- Denoising of Sensory Data by Maximum Likelihood Estimation of Sparse Components (1998) (8)
- Robust contrastive learning and nonlinear ICA in the presence of outliers (2019) (8)
- Noisy independent component analysis, maximum likelihood estimation, and competitive learning (1998) (8)
- Two Methods for Estimating Overcomplete Independent Component Bases (2001) (8)
- A unifying framework for natural image statistics: spatiotemporal activity bubbles (2004) (7)
- Receptive Fields Similar to Simple Cells Maximize Temporal Coherence in Natural Video (2002) (7)
- Interpretable brain age prediction using linear latent variable models of functional connectivity (2019) (7)
- Purely Logical Neural Principal Component and Independent Component Learning (1996) (7)
- SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling (2017) (7)
- A Bayesian inverse solution using independent component analysis (2014) (7)
- Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis (2016) (7)
- Discovery of Linear Non-Gaussian Acyclic Models in the Presence of Latent Classes (2007) (7)
- The Independence Assumption: Analyzing the Independence of the Components by Topography (2000) (7)
- Orthogonal Connectivity Factorization: Interpretable Decomposition of Variability in Correlation Matrices (2016) (7)
- From Neural Principal Components to Neural Independent Components (1997) (7)
- A Quasi-stochastic Gradient Algorithm for Variance-Dependent Component Analysis (2006) (6)
- Emergence of Linguistic Representations by Independent Component Analysis (2003) (6)
- Structural equations and divisive normalization for energy-dependent component analysis (2011) (6)
- New Permutation Algorithms for Causal Discovery Using ICA (2006) (6)
- Topography as a property of the natural sensory world (2002) (6)
- Independent innovation analysis for nonlinear vector autoregressive process (2020) (6)
- ICA by Minimization of Mutual Information (2002) (6)
- Regression using independent component analysis, and its connection to multi-layer perceptrons (1999) (6)
- Complex-Valued Independent Component Analysis of Natural Images (2011) (6)
- Sparse Regression: Utilizing the Higher-order Structure of Data for Prediction (1998) (6)
- Correlated topographic analysis: estimating an ordering of correlated components (2013) (6)
- Sparse and low-rank matrix regularization for learning time-varying Markov networks (2016) (5)
- Emergence of complex cell properties by decomposition of natural images into independent feature subspaces (1999) (5)
- Nonlinear Functional Causal Models for Distinguishing Cause from Effect (2016) (5)
- Mode-Seeking Clustering and Density Ridge Estimation via Direct Estimation of Density-Derivative-Ratios (2017) (5)
- ICA by Maximum Likelihood Estimation (2002) (5)
- Estimation of Non-Normalized Mixture Models (2019) (5)
- Independent Component Analysis.Japanese translation (2005) (5)
- Discovery of Exogenous Variables in Data with More Variables Than Observations (2009) (5)
- Neural-Kernelized Conditional Density Estimation (2018) (5)
- Spatiotemporal receptive fields maximizing temporal coherence in natural image sequences (2004) (4)
- Estimation of Causal Orders in a Linear Non-Gaussian Acyclic Model: A Method Robust against Latent Confounders (2012) (4)
- The Optimal Noise in Noise-Contrastive Learning Is Not What You Think (2022) (4)
- Emotional Disorders in Autonomous Agents? (1999) (4)
- Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations (2014) (4)
- Proc. Conf. on Uncertainty in Artificial Intelligence (UAI) (2010) (4)
- Learning with self-supervision on EEG data (2021) (4)
- A Non-Negative Sparse Coding Network Learns Contour Coding and Integration From Natural Images (2001) (3)
- Localization of the Resting State Vasomotor Fluctuation with FFT, Cross Correlation, Principal Component and Independent Component Analysis of fMRI data. (2001) (3)
- The Statistical Properties of Local Log-Contrast in Natural Images (2007) (3)
- Behavioral / Systems / Cognitive Representation of Cross-Frequency Spatial Phase Relationships in Human Visual Cortex (2009) (3)
- A two-layer temporal generative model of natural video exhibits complex-cell-like pooling of simple cell outputs (2003) (3)
- Learning a selectivity-invariance-selectivity feature extraction architecture for images (2012) (3)
- A Novel Temporal Generative Model of Natural Video as an Internal Model in Early Vision (2002) (3)
- Information criteria for non-normalized models (2019) (3)
- Processing of pragmatic communication in ASD: a video-based brain imaging study (2020) (3)
- Methods Using Time Structure (2002) (3)
- Simultaneous Estimation of Nongaussian Components and Their Correlation Structure (2015) (3)
- ON EXISTENCE AND UNIQUENESS OF SOLUTIONS IN NON-LINEAR INDEPENDENT COMPONENT ANALYSIS (1998) (3)
- Energy Correlations and Topographic Organization (2009) (3)
- Preface: The 2018 ACM SIGKDD Workshop on Causal Discovery (2018) (3)
- Topographic Analysis of Correlated Components (2012) (2)
- Fast and robust deflationary separation of complex valued signals (2000) (2)
- Bridging Information Criteria and Parameter Shrinkage for Model Selection (2013) (2)
- Shared Independent Component Analysis for Multi-Subject Neuroimaging (2021) (2)
- Lateral Interactions and Feedback (2009) (2)
- Learning encoding and decoding filters for data representation with a spiking neuron (2008) (2)
- New Approximations of Diierential Entropy for Independent Component Analysis and Projection Pursuit New Approximations of Diierential Entropy for Independent Component Analysis and Projection Pursuit New Approximations of Diierential Entropy for Independent Component Analysis and Projection Pursuit (1997) (2)
- Learning to Segment Any Random Vector (2006) (2)
- Learning reconstruction and prediction of natural stimuli by a population of spiking neurons (2009) (2)
- Sparse and Low-Rank Estimation of Time-Varying Markov Networks with Alternating Direction Method of Multipliers (2010) (2)
- On the learning of nonlinear visual features from natural images by optimizing response energies (2008) (2)
- Estimation of Non-Normalized Mixture Models and Clustering Using Deep Representation (2018) (2)
- ESTIMATION THEORY AND INFORMATION GEOMETRY BASED ON DENOIS ING (2008) (2)
- Overview and Comparison of Basic ICA Methods (2002) (2)
- Learning Topographic Representations for Linearly Correlated Components (2011) (2)
- Simultaneous blind separation and clustering of coactivated EEG/MEG sources for analyzing spontaneous brain activity (2014) (2)
- Decoding emotional valence from electroencephalographic rhythmic activity (2017) (2)
- Gradients and Optimization Methods (2002) (2)
- Dynamic connectivity factorization: Interpretable decompositions of non-stationarity (2014) (2)
- Chapter 6 – Iterative algorithms (2010) (2)
- ICA with Overcomplete Bases (2002) (2)
- Convolutive Mixtures and Blind Deconvolution (2002) (2)
- ICA by Tensorial Methods (2002) (1)
- Unsupervised learning of dependencies between local luminance and contrast in natural images (2008) (1)
- Activity bubbles and natural image sequences (2002) (1)
- Overcomplete and Non-negative Models (2009) (1)
- A Two-Layer Dynamic Generative Model of Natural Image Sequences (2002) (1)
- Statistical Estimation in Conceptual Spaces (1998) (1)
- Nonlinear Independent Component Analysis for Principled Disentanglement in Unsupervised Deep Learning (2023) (1)
- Representation of broadband edges and spatial phase congruency in human visual cortex (2010) (1)
- Identifiability of latent-variable and structural-equation models: from linear to nonlinear (2023) (1)
- Representation of spatial frequency in human retinotopic areas (2007) (1)
- Proc. Int. Joint Conference on Neural Networks (IJCNN) (2008) (1)
- 17th European Symposium on Artificial Neural Networks (ESANN) (2009) (1)
- Painful intelligence: What AI can tell us about human suffering (2022) (1)
- Workshop on Deep Learning and Unsupervised Feature Learning, NIPS (2011) (1)
- Nonlinear acyclic causal models (2010) (1)
- Maladaptive Emotion-Based Behaviors in Autonomous Agents (1998) (1)
- Characterization of Spontaneous Neuromagnetic Brain Rhythms Using Independent Component Analysis of Short-Time Fourier Transforms (2010) (1)
- Unsupervised representation learning of spontaneous MEG data with nonlinear ICA (2023) (1)
- Realizations of quantum computing using optical manipulations of atoms (2002) (1)
- A unified probabilistic model for independent and principal component analysis (2015) (1)
- Sparse Coding and Simple Cells (2009) (1)
- Chapter 2 Independent component analysis and blind source separation (2004) (0)
- Proc. Workshop on Information Theoretic Methods in Science and Engineering (WITMSE2013) (2013) (0)
- Temporal Sequences of Natural Images (2009) (0)
- Outline of the Visual System (2009) (0)
- Analysing spatiotemporal dynamics in contrast detection by Classification Images (2010) (0)
- NonSENS: Non-Linear SEM Estimation using Non-Stationarity (2018) (0)
- Linear Filters and Frequency Analysis (2009) (0)
- Correlated topographic analysis: estimating an ordering of correlated components (2013) (0)
- Learning spike-timings based representations of sensory stimuli with leaky integrate-and-fire neurons (2009) (0)
- Template optimization and transfer in perceptual learning. (2016) (0)
- Multivariate Probability and Statistics (2009) (0)
- Faculty Opinions recommendation of Divisive normalization in olfactory population codes. (2010) (0)
- PCA-based source-space contrast maps reveal psychologically meaningful individual differences in continuous MEG activity (2019) (0)
- Autoregressive flow-based causal discovery and inference (2020) (0)
- Proc. Asian Conference on Machine Learning (ACML) (2012) (0)
- Proc. of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning (AKRR) (2005) (0)
- Faculty Opinions recommendation of A comparative study of shape representation in macaque visual areas v2 and v4. (2007) (0)
- Dynamics of retinotopic spatial attention revealed by multifocal MEG (2022) (0)
- Independent component analysis with an inverse problem motivated penalty term (2015) (0)
- Faculty Opinions recommendation of Non-Bayesian contour synthesis. (2011) (0)
- Brain Imaging Applications (2002) (0)
- M L ] 5 J un 2 01 8 Neural-Kernelized Conditional Density Estimation (2018) (0)
- Energy Detectors and Complex Cells (2009) (0)
- Conclusion and Future Prospects (2009) (0)
- Faculty Opinions recommendation of Contrast gain control in natural scenes. (2008) (0)
- A LATENT VARIABLE MODEL FOR SIMULTANEOUS DIMENSIONALITY REDUCTION AND CONNECTIVITY ESTIMATION (2018) (0)
- Dependencies of Energy Detectors: Beyond V1 (2009) (0)
- Discovery of linear acyclic models in the presence of latent classes using ICA mixtures (2006) (0)
- Color and Stereo Images (2009) (0)
- Faculty Opinions recommendation of Spectral receptive field properties explain shape selectivity in area V4. (2006) (0)
- to Encode Surface Properties? Do Cortical Neurons Process Luminance or Contrast (2015) (0)
- Hidden Markov Nonlinear ICA: Unsupervised Learning from Nonstationary Time Series (2020) (0)
- Faculty Opinions recommendation of Parameter learning but not structure learning: a Bayesian network model of constraints on early perceptual learning. (2007) (0)
- Advances in statistical generative models (0)
- Across-channel dependencies between local luminance and con- trast in natural images (2007) (0)
- Information-Theoretic Interpretations (2009) (0)
- Faculty Opinions recommendation of Investigations into resting-state connectivity using independent component analysis. (2006) (0)
- MODELS OF IMAGES AND EARLY VISION (2005) (0)
- Crash Course on Linear Algebra (2009) (0)
- F1000Prime recommendation of Unsupervised natural visual experience rapidly reshapes size-invariant object representation in inferior temporal cortex. (2010) (0)
- Characterising subjecto-to-subject variability of brain connectivity with constrained principal component analysis (2017) (0)
- Adaptive cognitive systems (2004) (0)
- Sparse and low-rank matrix regularization for learning time-varying Markov networks (2016) (0)
- The Discrete Fourier Transform (2009) (0)
- SPATIOTEMPORAL LINEAR SIMPLE-CELL MODELS BASED ON TEMPORAL COHERENCE AND INDEPENDENT COMPONENT ANALYSIS (2004) (0)
- Unsupervised learning of an embodied representation for action selection (2007) (0)
- Exploring the spatiotemporal dynamics of brightness perception by reverse correlation (2010) (0)
- Natural image statistics: Energy-based models estimated by score matching (2009) (0)
- Behavioural priors : Learning to search efficiently in action planning (2007) (0)
- Learning Data Representation with a Population of Spiking Neurons as Encoder (2007) (0)
- advancescomponent analysis: recent (2013) (0)
- Faculty Opinions recommendation of Network modelling methods for FMRI. (2010) (0)
- Faculty Opinions recommendation of Optimal decoding of correlated neural population responses in the primate visual cortex. (2006) (0)
- Direction Matters: On Influence-Preserving Graph Summarization and Max-Cut Principle for Directed Graphs (2019) (0)
- ICA by Nonlinear Decorrelation and Nonlinear PCA (2002) (0)
- Using classification images to reveal the critical features in global shape perception (2010) (0)
- Energy Correlation of Linear Features and Normalization (2009) (0)
- Supplementary Material for Nonlinear ICA of Temporally Dependent Stationary Sources (2017) (0)
- Wavelets and Natural Image (1997) (0)
- 17th International Conference on Biomagnetism Advances in Biomagnetism, Biomag2010, Dubrovnik, Croatia, 28.3.-1.4.2010 (2010) (0)
- Extending Neural ICA and Blind Source Separation for Nonlinear Data Models (1998) (0)
- Estimating signal-adapted wavelets using sparseness criteria (1999) (0)
- Feature Extraction by ICA (2002) (0)
- Random Vectors and Independence (2002) (0)
- Features in V1 Speed Dependence of Tuning to One-Dimensional (2007) (0)

This paper list is powered by the following services:

## Other Resources About Aapo Hyvärinen

## What Schools Are Affiliated With Aapo Hyvärinen?

Aapo Hyvärinen is affiliated with the following schools: