Simo Särkkä

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Arno SolinAssistant 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
Aki VehtariProfessor, Aalto UniversityVerified email at aalto.fi
Zheng ZhaoAssistant professor, Linköping UniversityVerified email at liu.se
Toni KarvonenAssociate Professor, LUT UniversityVerified email at lut.fi
Ángel F. García-FernándezSenior Lecturer (Associate Professor), University of Liverpool, United KingdomVerified email at liverpool.ac.uk
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
Philipp HennigUniversity of TübingenVerified email at uni-tuebingen.de
Fa-Hsuan LinSunnybrook Research Institute; University of TorontoVerified email at sri.utoronto.ca
Isambi Sailon MbalawataUniversity of Dar es SalamVerified email at maths.udsm.ac.tz
Toni AuranenStaff Scientist, Aalto NeuroImaging, Aalto UniversityVerified email at aalto.fi
Adrien CorenflosPostdoctoral researcher, University of WarwickVerified email at warwick.ac.uk
Simon GodsillUniversity of CambridgeVerified email at eng.cam.ac.uk
Robert PicheTampere University of TechnologyVerified email at tuni.fi
Ali Bahrami RadAssistant Professor, Emory UniversityVerified email at dbmi.emory.edu
Muhammad Fuady EmzirKing Fahd University of Petroleum and Minerals, IRC Smart Mobility and LogisticsVerified email at kfupm.edu.sa

Simo Särkkä

Professor, Aalto University

Verified email at aalto.fi - Homepage

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


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Bayesian filtering and smoothing S Särkkä Cambridge University Press, 2013	2992*	2013
On unscented Kalman filtering for state estimation of continuous-time nonlinear systems S Sarkka IEEE Transactions on automatic control 52 (9), 1631-1641, 2007	718	2007
Recursive noise adaptive Kalman filtering by variational Bayesian approximations S Sarkka, A Nummenmaa IEEE Transactions on Automatic control 54 (3), 596-600, 2009	715	2009
Applied stochastic differential equations S Särkkä, A Solin Cambridge University Press, 2019	624	2019
Rao-Blackwellized particle filter for multiple target tracking S Sarkka, A Vehtari, J Lampinen Information Fusion 8 (1), 2-15, 2007	394	2007
Unscented rauch--tung--striebel smoother S Särkkä IEEE transactions on automatic control 53 (3), 845-849, 2008	377	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	355*	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	311	2010
Spatiotemporal learning via infinite-dimensional Bayesian filtering and smoothing: A look at Gaussian process regression through Kalman filtering S Särkkä, A Solin, J Hartikainen IEEE Signal Processing Magazine 30 (4), 51-61, 2013	291	2013
Hilbert space methods for reduced-rank Gaussian process regression A Solin, S Särkkä Statistics and Computing 30 (2), 419-446, 2020	266	2020
Recursive Bayesian inference on stochastic differential equations S Särkkä Dissertation Abstracts International, 2006	214	2006
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	206	2020
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	185	2012
Sensors and AI techniques for situational awareness in autonomous ships: A review S Thombre, Z Zhao, H Ramm-Schmidt, JMV García, T Malkamäki, ... IEEE transactions on intelligent transportation systems 23 (1), 64-83, 2020	173	2020
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	169	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	153	2018
Linear operators and stochastic partial differential equations in Gaussian process regression S Särkkä Artificial Neural Networks and Machine Learning–ICANN 2011: 21st …, 2011	151	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	148	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	139	2015
Gaussian filtering and smoothing for continuous-discrete dynamic systems S Särkkä, J Sarmavuori Signal Processing 93 (2), 500-510, 2013	129	2013

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