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Aapo Hyvärinen

Inria, Université-Paris Saclay, Saclay, France, University of Helsinky, Finland

Adaptive Multi-View ICA: Estimation of noise levels for optimal inference


Feb 22, 2021
Hugo Richard, Pierre Ablin, Aapo Hyvärinen, Alexandre Gramfort, Bertrand Thirion


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Causal Autoregressive Flows


Nov 04, 2020
Ilyes Khemakhem, Ricardo Pio Monti, Robert Leech, Aapo Hyvärinen


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Uncovering the structure of clinical EEG signals with self-supervised learning


Jul 31, 2020
Hubert Banville, Omar Chehab, Aapo Hyvärinen, Denis-Alexander Engemann, Alexandre Gramfort

* 32 pages, 9 figures 

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Relative gradient optimization of the Jacobian term in unsupervised deep learning


Jun 26, 2020
Luigi Gresele, Giancarlo Fissore, Adrián Javaloy, Bernhard Schölkopf, Aapo Hyvärinen


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Hidden Markov Nonlinear ICA: Unsupervised Learning from Nonstationary Time Series


Jun 22, 2020
Hermanni Hälvä, Aapo Hyvärinen

* Accepted for publication at UAI 2020 

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Independent innovation analysis for nonlinear vector autoregressive process


Jun 19, 2020
Hiroshi Morioka, Aapo Hyvärinen


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Modeling Shared Responses in Neuroimaging Studies through MultiView ICA


Jun 12, 2020
Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin


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ICE-BeeM: Identifiable Conditional Energy-Based Deep Models


Feb 26, 2020
Ilyes Khemakhem, Ricardo Pio Monti, Diederik P. Kingma, Aapo Hyvärinen


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Self-supervised representation learning from electroencephalography signals


Nov 13, 2019
Hubert Banville, Isabela Albuquerque, Aapo Hyvärinen, Graeme Moffat, Denis-Alexander Engemann, Alexandre Gramfort


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Robust contrastive learning and nonlinear ICA in the presence of outliers


Nov 01, 2019
Hiroaki Sasaki, Takashi Takenouchi, Ricardo Monti, Aapo Hyvärinen


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Direction Matters: On Influence-Preserving Graph Summarization and Max-cut Principle for Directed Graphs


Jul 22, 2019
Wenkai Xu, Gang Niu, Aapo Hyvärinen, Masashi Sugiyama


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Variational Autoencoders and Nonlinear ICA: A Unifying Framework


Jul 10, 2019
Ilyes Khemakhem, Diederik P. Kingma, Aapo Hyvärinen


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Neural-Kernelized Conditional Density Estimation


Jun 05, 2018
Hiroaki Sasaki, Aapo Hyvärinen


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


May 24, 2018
Ricardo Pio Monti, Aapo Hyvärinen

* 13 pages, 6 figures. To appear in UAI 2018 

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Deep Energy Estimator Networks


May 21, 2018
Saeed Saremi, Arash Mehrjou, Bernhard Schölkopf, Aapo Hyvärinen


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


Mar 30, 2018
Hiroaki Sasaki, Takafumi Kanamori, Aapo Hyvärinen, Gang Niu, Masashi Sugiyama


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Simultaneous Estimation of Non-Gaussian Components and their Correlation Structure


Jul 27, 2017
Hiroaki Sasaki, Michael U. Gutmann, Hayaru Shouno, Aapo Hyvärinen


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Density Estimation in Infinite Dimensional Exponential Families


May 26, 2017
Bharath Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Aapo Hyvärinen, Revant Kumar

* 58 pages, 8 figures; Fixed some errors and typos 

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Clustering via Mode Seeking by Direct Estimation of the Gradient of a Log-Density


Apr 20, 2014
Hiroaki Sasaki, Aapo Hyvärinen, Masashi Sugiyama


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