World's Best Scientists 2026 revealed!
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Computer Science
Finland
2026

D-Index & Metrics

Computer Science

D-Index
73
Citations
78162
World Ranking
1531
National Ranking
7

Research.com Recognitions

  • 2026 - Research.com Computer Science in Finland Leader Award
  • 2025 - Research.com Computer Science in Finland Leader Award
  • 2022 - Research.com Computer Science in Finland Leader Award

Overview

Aapo Hyvärinen is affiliated with the University of Helsinki in Finland. Their research primarily spans the fields of computer science and neuroscience, with significant contributions to cognitive neuroscience, artificial intelligence, and signal processing.

Their work addresses various topics including:

  • Blind Source Separation Techniques
  • Neural Networks and Applications
  • Functional Brain Connectivity Studies
  • Neural dynamics and brain function
  • EEG and Brain-Computer Interfaces
  • Spectroscopy and Chemometric Analyses
  • Bayesian Modeling and Causal Inference

Among recent publications, the following papers are notable:

  • "Uncovering the structure of clinical EEG signals with self-supervised learning," 2020, arXiv (Cornell University)
  • "Brain activity reflects the predictability of word sequences in listened continuous speech," 2020, NeuroImage
  • "Nonlinear ICA of fMRI reveals primitive temporal structures linked to rest, task, and behavioral traits," 2020, NeuroImage
  • "ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA," 2020, arXiv (Cornell University)
  • "Interpretable brain age prediction using linear latent variable models of functional connectivity," 2020, PLoS ONE

Frequent co-authors include:

  • Alexandre Gramfort
  • Ilyes Khemakhem
  • Omar Chehab
  • Hiroshi Morioka
  • Hermanni Hälvä

The primary venues where this researcher frequently publishes are:

  • arXiv (Cornell University)
  • NeuroImage
  • Helda (University of Helsinki)
  • Annals of the Institute of Statistical Mathematics
  • Imaging Neuroscience

Best Publications

  • Independent component analysis: algorithms and applications

    A. Hyvärinen;E. Oja

  • Fast and robust fixed-point algorithms for independent component analysis

    A. Hyvarinen

  • Independent Component Analysis

    Aapo Hyvarinen;Juha Karhunen;Erkki Oja

  • Independent Component Analysis

    Unknown

  • A fast fixed-point algorithm for independent component analysis

    Aapo Hyvärinen;Erkki Oja

  • Survey on Independent Component Analysis

    A. Hyvärinen

  • Noise-contrastive estimation: A new estimation principle for unnormalized statistical models

    Michael Gutmann;Aapo Hyvärinen

  • Validating the independent components of neuroimaging time series via clustering and visualization.

    Johan Himberg;Aapo Hyvärinen;Fabrizio Esposito

  • A Linear Non-Gaussian Acyclic Model for Causal Discovery

    Shohei Shimizu;Patrik O. Hoyer;Aapo Hyvärinen;Antti Kerminen

  • A fast fixed-point algorithm for independent component analysis of complex valued signals.

    Ella Bingham;Aapo Hyvärinen

  • Estimation of Non-Normalized Statistical Models by Score Matching

    Aapo Hyvärinen

  • Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics

    Michael U. Gutmann;Aapo Hyvärinen

  • Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces

    Aapo Hyvärinen;Patrik Hoyer

  • New Approximations of Differential Entropy for Independent Component Analysis and Projection Pursuit

    Aapo Hyvärinen

  • Nonlinear independent component analysis: existence and uniqueness results

    Aapo Hyvärinen;Petteri Pajunen

  • Topographic Independent Component Analysis

    Aapo Hyvärinen;Patrik O. Hoyer;Mika O. Inki

  • Sparse code shrinkage: denoising of nongaussian data by maximum likelihood estimation

    Aapo Hyvärinen

  • Independent component analysis of nondeterministic fMRI signal sources.

    Vesa Kiviniemi;Juha-Heikki Kantola;Jukka Jauhiainen;Aapo Hyvärinen

  • Independent component analysis: recent advances.

    Aapo Hyvärinen

  • Independent component analysis of fMRI group studies by self-organizing clustering

    Fabrizio Esposito;Tommaso Scarabino;Aapo Hyvarinen;Johan Himberg

  • DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model

    Shohei Shimizu;Takanori Inazumi;Yasuhiro Sogawa;Aapo Hyvärinen

  • Natural Image Statistics

    Aapo Hyvärinen;Jarmo Hurri;Patrik O. Hoyer

  • On the identifiability of the post-nonlinear causal model

    Kun Zhang;Aapo Hyvärinen

  • Variational Autoencoders and Nonlinear ICA: A Unifying Framework

    Ilyes Khemakhem;Diederik P. Kingma;Ricardo Pio Monti;Aapo Hyvarinen;Aapo Hyvarinen

Frequent Co-Authors

Patrik O. Hoyer
Patrik O. Hoyer University of Helsinki
Erkki Oja
Erkki Oja Aalto University
Juha Karhunen
Juha Karhunen Aalto University
Kun Zhang
Kun Zhang Carnegie Mellon University
Lauri Parkkonen
Lauri Parkkonen Aalto University
Motoaki Kawanabe
Motoaki Kawanabe Advanced Telecommunications Research Institute International
Riitta Hari
Riitta Hari Aalto University
Vesa Kiviniemi
Vesa Kiviniemi Oulu University Hospital

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