Neuroinformatics research group / Aapo Hyvärinen

Publications

Research output per year 1999 2015 2016 2017 2019 2024

• 25 Article
• 15 Conference contribution
• 2 Chapter

Research output per year

Research output per year

Search results

• 2024

  Improving source estimation of retinotopic MEG responses by combining data from multiple subjects

  Hietala, P., Kurki, I. J. A., Hyvärinen, A. J. & Henriksson, L., 2024, In: Imaging Neuroscience. 2, p. 1-15 15 p.

  Research output: Contribution to journal › Article › Scientific › peer-review

  Open Access

  File
• 2023

  Unsupervised representation learning of spontaneous MEG data with nonlinear ICA

  Zhu, Y., Parviainen, T., Heinilä, E., Parkkonen, L. & Hyvärinen, A., 1 Jul 2023, In: NeuroImage. 274, 13 p.

  Research output: Contribution to journal › Article › Scientific › peer-review

  Open Access

  File
• 2020

  Nonlinear ICA of fMRI reveals primitive temporal structures linked to rest, task, and behavioral traits

  Morioka, H., Calhoun, V. & Hyvarinen, A., Sept 2020, In: NeuroImage. 218, 17 p., 116989.

  Research output: Contribution to journal › Article › Scientific › peer-review

  Open Access

  File
• 2019

  Causal Discovery with General Non-Linear Relationships Using Non-Linear ICA

  Monti, R. P., Zhang, K. & Hyvärinen, A., 2019, Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, UAI 2019, Tel Aviv, Israel, July 22-25, 2019. AUAI Press / Association for Uncertainty in Artificial Intelligence, 10 p. (Conference on Uncertainty in Artificial Intelligence).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  File

• Estimation of Non-Normalized Mixture Models and Clustering Using Deep Representation

  Matsuda, T. & Hyvärinen, A., 2019, The 22nd International Conference on Artificial Intelligence and Statistics, 16-18 April 2019. Chaudhuri, K. & Sugiyama , M. (eds.). Cambridge, MA: Journal of Machine Learning Research, p. 2555-2563 9 p. (Proceedings of Machine Learning Research; vol. 89).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  File

• Neural Empirical Bayes

  Saremi, S. & Hyvärinen, A., 2019, In: Journal of Machine Learning Research. 20, 23 p., 181.

  Research output: Contribution to journal › Article › Scientific › peer-review

  Open Access

  File

• Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning

  Hyvärinen, A., Sasaki, H. & Turner, R. E., 2019, The 22nd International Conference on Artificial Intelligence and Statistics, 16-18 April 2019. Chaudhuri, K. & Sugiyama , M. (eds.). Cambridge, MA: Journal of Machine Learning Research, p. 859-868 10 p. (Proceedings of Machine Learning Research ; vol. 89).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  File

• Self-supervised representation learning from electroencephalography signals

  Banville, H., Albuquerque, I., Hyvärinen, A., Moffat, G., Engemann, D.-A. & Gramfort, A., 2019, 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, Vol. 2019. 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  File
• 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 proceeding › Conference contribution › Scientific › peer-review

  Open Access

  File

• 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 journal › Article › Scientific › peer-review

  Open Access

  File
• 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 journal › Article › Scientific › peer-review

  Open Access

  File

• 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 journal › Article › Scientific › peer-review

  Open Access

  File

• 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 journal › Article › Scientific › peer-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 proceeding › Conference contribution › Scientific › peer-review

  Open Access

  File

• Prediction of active peak force using a multilayer perceptron

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

  Research output: Contribution to journal › Article › Scientific › peer-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 journal › Article › Scientific › peer-review

  Open Access

  File

• 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 proceeding › Conference contribution › Scientific › peer-review

  Open Access

  File
• 2016

  Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis

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

  Research output: Contribution to journal › Article › Scientific › peer-review

  Open Access

  File

• Disambiguating the role of noise correlations when decoding neural populations together

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

  Research output: Contribution to journal › Article › Scientific › peer-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 journal › Article › Scientific › peer-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 proceeding › Chapter › Scientific › peer-review

• Orthogonal Connectivity Factorization: Interpretable Decomposition of Variability in Correlation Matrices

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

  Research output: Contribution to journal › Article › Scientific › peer-review

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

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

  Research output: Contribution to journal › Article › Scientific › peer-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 journal › Article › Scientific › peer-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 journal › Article › Scientific › peer-review

  Open Access

  File

• 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 proceeding › Conference contribution › Scientific › peer-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 proceeding › Chapter › Scientific

• 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 journal › Article › Scientific › peer-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 journal › Article › Scientific › peer-review

  Open Access

  File

• 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 journal › Article › Scientific › peer-review

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

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

  Research output: Contribution to journal › Article › Scientific › peer-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 journal › Article › Scientific › peer-review

  Open Access

  File

• 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 proceeding › Conference contribution › Scientific › peer-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 journal › Article › Scientific › peer-review

  Open Access

  File

• 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 journal › Article › Scientific › peer-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 proceeding › Conference contribution › Scientific › peer-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 journal › Article › Scientific › peer-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 proceeding › Conference contribution › Scientific › peer-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 proceeding › Conference contribution › Scientific › peer-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 proceeding › Conference contribution › Scientific › peer-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 proceeding › Conference contribution › Scientific › peer-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 proceeding › Conference contribution › Scientific › peer-review