Simo Särkkä

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Arno SolinAssociate Professor in Machine Learning, Aalto UniversityVerified email at aalto.fi
Filip TronarpAssociate Senior Lecturer / Assistant Professor, Lund UniversityVerified email at matstat.lu.se
Lennart SvenssonProfessor in Signal Processing, Chalmers University of TechnologyVerified email at chalmers.se
Zheng ZhaoAssistant professor, Linköping UniversityVerified email at liu.se
Aki VehtariProfessor, Aalto UniversityVerified email at aalto.fi
Ángel F. García-FernándezAssociate Professor, Universidad Politécnica de Madrid, SpainVerified email at upm.es
Toni KarvonenAssociate Professor in Applied Mathematics, LUT UniversityVerified email at lut.fi
Roland HostettlerAssociate Professor, Uppsala UniversityVerified email at angstrom.uu.se
Jouko LampinenAalto UniversityVerified email at aalto.fi
Juho KannalaAssociate Professor, Aalto University & University of Oulu, FinlandVerified email at aalto.fi
Thomas SchönProfessor, Uppsala UniversityVerified email at it.uu.se
Fa-Hsuan LinSunnybrook Research Institute; University of TorontoVerified email at sri.utoronto.ca
Adrien CorenflosPostdoctoral researcher, University of WarwickVerified email at warwick.ac.uk
Isambi Sailon MbalawataUniversity of Dar es SalamVerified email at maths.udsm.ac.tz
Toni AuranenStaff Scientist, Aalto NeuroImaging, Aalto UniversityVerified email at aalto.fi
Philipp HennigUniversity of TübingenVerified email at uni-tuebingen.de
Simon GodsillUniversity of CambridgeVerified email at eng.cam.ac.uk
Juho KokkalaVerified email at aalto.fi
Ali Bahrami RadAssistant Professor, Emory UniversityVerified email at dbmi.emory.edu
Robert PicheTampere UniversityVerified email at tuni.fi

Simo Särkkä

Professor, Aalto University

Verified email at aalto.fi - Homepage

multi-sensor data fusion Bayesian filtering and smoothing sensor fusion medical technology AI


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Bayesian filtering and smoothing S Särkkä Cambridge University Press, 2013	3145*	2013
Recursive noise adaptive Kalman filtering by variational Bayesian approximations S Sarkka, A Nummenmaa IEEE Transactions on Automatic control 54 (3), 596-600, 2009	749	2009
On unscented Kalman filtering for state estimation of continuous-time nonlinear systems S Sarkka IEEE Transactions on automatic control 52 (9), 1631-1641, 2007	732	2007
Applied stochastic differential equations S Särkkä, A Solin Cambridge University Press, 2019	726	2019
Rao-Blackwellized particle filter for multiple target tracking S Sarkka, A Vehtari, J Lampinen Information Fusion 8 (1), 2-15, 2007	400	2007
Unscented rauch--tung--striebel smoother S Särkkä IEEE transactions on automatic control 53 (3), 845-849, 2008	395	2008
Optimal filtering with Kalman filters and smoothers–a Manual for Matlab toolbox EKF/UKF J Hartikainen, A Solin, S Särkkä Biomedical Engineering, 1-57, 2008	373*	2008
Kalman filtering and smoothing solutions to temporal Gaussian process regression models J Hartikainen, S Särkkä 2010 IEEE international workshop on machine learning for signal processing …, 2010	333	2010
Spatiotemporal learning via infinite-dimensional Bayesian filtering and smoothing: A look at Gaussian process regression through Kalman filtering S Sarkka, A Solin, J Hartikainen IEEE Signal Processing Magazine 30 (4), 51-61, 2013	307	2013
Hilbert space methods for reduced-rank Gaussian process regression A Solin, S Särkkä Statistics and Computing 30 (2), 419-446, 2020	286	2020
A survey of Monte Carlo methods for parameter estimation D Luengo, L Martino, M Bugallo, V Elvira, S Särkkä EURASIP Journal on Advances in Signal Processing 2020, 1-62, 2020	235	2020
Sensors and AI techniques for situational awareness in autonomous ships: A review S Thombre, Z Zhao, H Ramm-Schmidt, JMV Garcia, T Malkamäki, ... IEEE transactions on intelligent transportation systems 23 (1), 64-83, 2020	228	2020
Recursive Bayesian inference on stochastic differential equations S Särkkä Dissertation Abstracts International, 2006	214	2006
Recursive outlier-robust filtering and smoothing for nonlinear systems using the multivariate Student-t distribution R Piché, S Särkkä, J Hartikainen 2012 IEEE International Workshop on Machine Learning for Signal Processing, 1-6, 2012	196	2012
Modeling and interpolation of the ambient magnetic field by Gaussian processes A Solin, M Kok, N Wahlström, TB Schön, S Särkkä IEEE Transactions on robotics 34 (4), 1112-1127, 2018	174	2018
Dynamic retrospective filtering of physiological noise in BOLD fMRI: DRIFTER S Särkkä, A Solin, A Nummenmaa, A Vehtari, T Auranen, S Vanni, FH Lin NeuroImage 60 (2), 1517-1527, 2012	172	2012
Linear operators and stochastic partial differential equations in Gaussian process regression S Särkkä Artificial Neural Networks and Machine Learning–ICANN 2011: 21st …, 2011	164	2011
Batch Continuous-Time Trajectory Estimation as Exactly Sparse Gaussian Process Regression. TD Barfoot, CH Tong, S Särkkä Robotics: Science and Systems 10, 1-10, 2014	154	2014
Posterior linearization filter: Principles and implementation using sigma points ÁF García-Fernández, L Svensson, MR Morelande, S Särkkä IEEE transactions on signal processing 63 (20), 5561-5573, 2015	144	2015
Non-linear noise adaptive Kalman filtering via variational Bayes S Särkkä, J Hartikainen 2013 IEEE International Workshop on Machine Learning for Signal Processing …, 2013	133	2013

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