Neuroinformatics research group / Aapo Hyvärinen

  • PL 68 (Gustaf Hällströmin katu 2b), B326

    HELSINGIN YLIOPISTO

    Finland

Publications 1999 2018

2018

A Unified Probabilistic Model for Learning Latent Factors and Their Connectivities from High-Dimensional Data

Monti, R. P. & Hyvärinen, A., 6 Aug 2018, Uncertainty in Artificial Intelligence: Proceedings of the Thirty-Fourth Conference (2018). Globerson, A. & Silva, R. (eds.). Oregon: AUAI Press, p. 300-309 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Mode-Seeking Clustering and Density Ridge Estimation via Direct Estimation of Density-Derivative-Ratios

Sasaki, H., Kanamori, T., Hyvärinen, A., Niu, G. & Sugiyama, M., 2018, In : Journal of Machine Learning Research. 18, 47 p., 1.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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2017

A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing

Hosoya, H. & Hyvärinen, A., Jul 2017, In : PLoS Computational Biology. 13, 7, 27 p., 1005667.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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Collaborative roles of Temporoparietal Junction and Dorsolateral Prefrontal Cortex in Different Types of Behavioural Flexibility

Tei, S., Fujino, J., Kawada, R., Jankowski, K. F., Kauppi, J-P., van den Bos, W., Abe, N., Sugihara, G., Miyata, J., Murai, T. & Takahashi, H., 25 Jul 2017, In : Scientific Reports. 7, 8 p., 6415.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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Functional Brain Segmentation Using Inter-Subject Correlation in fMRI

Kauppi, J-P., Pajula, J., Niemi, J., Hari, R. & Tohka, J., May 2017, In : Human Brain Mapping. 38, 5, p. 2643-2665 23 p.

Research output: Contribution to journalArticleScientificpeer-review

Nonlinear ICA of Temporally Dependent Stationary Sources

Hyvärinen, A. & Morioka, H., 2017, Articial Intelligence and Statistics (AISTATS 2017). Singh, A. & Zhu, J. (eds.). Microtome Publishing, p. 460-469 10 p. (Proceedings of Machine Learning Research; vol. 54).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
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Prediction of active peak force using a multilayer perceptron

Niemelä, M., Kulmala, J-P., Kauppi, J-P., Kosonen, J. & Äyrämö, S., Sep 2017, In : Sports Engineering. 20, 3, p. 213-219

Research output: Contribution to journalArticleScientificpeer-review

Simultaneous Estimation of Nongaussian Components and Their Correlation Structure

Sasaki, H., Gutmann, M. U., Shouno, H. & Hyvärinen, A., Nov 2017, In : Neural Computation. 29, 11, p. 2887-2924 38 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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SPLICE: Fully tractable hierarchical extension of ICA with pooling

Hirayama, J., Hyvärinen, A. J. & Kawanabe, M., 2017, Proceedings of the 34 th International Conference on Machine Learning, Sydney, Australia. Precup, D. & Teh, Y. W. (eds.). International Machine Learning Society (IMLS), p. 2351-2362 12 p. (Proceedings of Machine Learning Research; vol. 70).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2016

Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis

Hirayama, J., Hyvarinen, A., Kiviniemi, V., Kawanabe, M. & Yamashita, O., 21 Dec 2016, In : PLoS One. 11, 12, 24 p., 0168180.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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Disambiguating the role of noise correlations when decoding neural populations together

Eyherabide, H. G., 2016, (Submitted) In : Neural Networks.

Research output: Contribution to journalArticleScientificpeer-review

Learning Visual Spatial Pooling by Strong PCA Dimension Reduction

Hosoya, H. & Hyvärinen, A., Jul 2016, In : Neural Computation. 28, 7, p. 1249-1264 16 p.

Research output: Contribution to journalArticleScientificpeer-review

Nonlinear Functional Causal Models for Distinguishing Cause from Effect

Hyvärinen, A. & Zhang, K., 2016, Statistics and Causality: Methods for Applied Empirical Research. Wiedermann, W. & von Eye, A. (eds.). 2016 ed. Hoboken, New Jersey : John Wiley, p. 185-201 17 p. (Wiley series in probability and statistics).

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Orthogonal Connectivity Factorization: Interpretable Decomposition of Variability in Correlation Matrices

Hyvärinen, A., Hirayama, J., Kiviniemi, V. & Kawanabe, M., Mar 2016, In : Neural Computation. 28, 3, p. 445-484 40 p.

Research output: Contribution to journalArticleScientificpeer-review

Sparse and low-rank matrix regularization for learning time-varying Markov networks

Hirayama, J., Hyvarinen, A. & Ishii, S., Dec 2016, In : Machine Learning. 105, 3, p. 335-366 32 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access

Spectators' Aesthetic Experience of Sound and Movement in Dance Performance: A Transdisciplinary Investigation

Reason, M., Jola, C., Kay, R., Reynolds, D., Kauppi, J-P., Grobras, M-H., Tohka, J. & Pollick, F. E., Feb 2016, In : Psychology of Aesthetics, Creativity and the Arts. 10, 1, p. 42-55 14 p.

Research output: Contribution to journalArticleScientificpeer-review

Template optimization and transfer in perceptual learning

Kurki, I., Hyvärinen, A. & Saarinen, J., Aug 2016, In : Journal of Vision. 16, 10, 18 p., 16.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA

Hyvärinen, A. & Morioka, H., 2016, Advances in Neural Information Processing Systems. Garnett, R., Lee, D. D., von Luxburg, U., Guyon, I. & Sugiyama, M. (eds.). Neural Information Processing Systems Foundation, p. 3772-3780 9 p. (Advances in neural information processing systems; vol. 29, no. NIPS 2016).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2015

A unified probabilistic model for independent and principal component analysis

Hyvärinen, A. J., 2015, Advances in Independent Component Analysis and Learning Machines. Bingham, E., Kaski, S., Laaksonen, J. & Lampinen, J. (eds.). Amsterdam: Elsevier Scientific Publ. Co, p. 75-82 8 p.

Research output: Chapter in Book/Report/Conference proceedingChapterScientific

Differences in fMRI intersubject correlation while viewing unedited and edited videos of dance performance

Herbec, A., Kauppi, J-P., Jola, C., Tohka, J. & Pollick, F. E., Oct 2015, In : Cortex. 71, p. 341-348 8 p.

Research output: Contribution to journalArticleScientificpeer-review

Three-Way Analysis of Spectrospatial Electromyography Data: Classification and Interpretation

Kauppi, J-P., Hahne, J., Müller, K-R. & Müller, K-R., 3 Jun 2015, In : PLoS One. 10, 6, 17 p., 0127231.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals

Kauppi, J-P., Kandemir, M., Saarinen, V-M., Hirvenkari, L., Parkkonen, L., Klami, A., Hari, R. & Kaski, S., 15 May 2015, In : NeuroImage. 112, p. 288-298 11 p.

Research output: Contribution to journalArticleScientificpeer-review

Unifying Blind Separation and Clustering for Resting-State EEG/MEG Functional Connectivity Analysis

Hirayama, J., Ogawa, T. & Hyvärinen, A., Jul 2015, In : Neural Computation. 27, 7, p. 1373-1404 32 p.

Research output: Contribution to journalArticleScientificpeer-review

2014

A versatile software package for inter-subject correlation based analyses of fMRI

Kauppi, J-P., Pajula, J. & Tohka, J., 31 Jan 2014, In : Frontiers in neuroinformatics. 8, 13 p., 2.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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Dynamic Connectivity Factorization: Interpretable decompositions of non-stationarity

Hyvärinen, A., Hirayama, J. & Kawanabe, M., 2014, 2014 International Workshop on Pattern Recognition in Neuroimaging PRNI 2014: Proceedings, 4-6 June 2014 Tubingen, Germany. IEEE, 4 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Group-PCA for very large fMRI datasets

Smith, S. M., Hyvärinen, A., Varoquaux, G., Miller, K. L. & Beckmann, C. F., 1 Nov 2014, In : NeuroImage. 101, p. 738-749 12 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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Investigating shape perception by classification images

Kurki, I., Saarinen, J. & Hyvarinen, A., 2014, In : Journal of Vision. 14, 12, 19 p., 24.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File
2012

Estimation of causal orders in a linear non-gaussian acyclic model: a method robust against latent confounders

Tashiro, T., Shimizu, S., Hyvärinen, A. & Washio, T., 2012, Artificial Neural Networks and Machine Learning – ICANN 2012: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings. Vol. 1. p. 491-498 8 p. (Lecture Notes in Computer Science; vol. 7552).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2011

DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model

Shimizu, S., Inazumi, T., Sogawa, Y., Hyvärinen, A., Kawahara, Y., Washio, T., Hoyer, P. & Bollen, K., 2011, In : Journal of Machine Learning Research. 12, 24 p.

Research output: Contribution to journalArticleScientificpeer-review

Hermite Polynomials and Measures of Non-Gaussianity

Puuronen, J. S. & Hyvärinen, A., 2011, Proc. Int. Conf. on Artificial Neural Networks (ICANN2011). p. 205--212

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2010

A Family of Computationally Efficient and Simple Estimators for Unnormalized Statistical Models

Pihlaja, M., Gutmann, M. U. & Hyvärinen, A. J., 2010, Conference on Uncertainty in Artificial Intelligence. 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

File
2004

Independent Component Analysis of Word Contexts and Comparison with Traditional Categories

Väyrynen, J. J., Honkela, T. & Hyvärinen, A., 1 Jun 2004, Unknown host publication. p. 300-303 4 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Linguistic Feature Extraction using Independent Component Analysis

Honkela, T. & Hyvärinen, A., 1 Jul 2004, Unknown host publication. p. 279-284 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

1999

Emotional Disorders in Autonomous Agents?

Hyvärinen, A. & Honkela, T., 1999, Unknown host publication. p. 350-354 5 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review