Simo Särkkä

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Arno SolinAssistant Professor in Machine Learning, Aalto UniversityVerified email at aalto.fi
Filip TronarpPostdoctoral researcher, Eberhard Karls University of TübingenVerified email at uni-tuebingen.de
Aki VehtariAssociate Professor, Aalto UniversityVerified email at aalto.fi
Toni KarvonenPostdoctoral Researcher, University of HelsinkiVerified email at helsinki.fi
Roland HostettlerAssistant Professor, Uppsala UniversityVerified email at angstrom.uu.se
Ángel F. García-FernándezLecturer (Assistant Professor), University of Liverpool, United KingdomVerified email at liverpool.ac.uk
Jouko LampinenAalto UniversityVerified email at aalto.fi
Zheng ZhaoUppsala UniversityVerified email at it.uu.se
Lennart SvenssonProfessor in Signal Processing, Chalmers University of TechnologyVerified email at chalmers.se
Juho KannalaAssistant Professor, Aalto University, 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
Isambi Sailon MbalawataUniversity of Dar es SalamVerified email at maths.udsm.ac.tz
Toni AuranenStaff Scientist, Aalto NeuroImaging, Aalto UniversityVerified email at aalto.fi
Simon GodsillUniversity of CambridgeVerified email at eng.cam.ac.uk
Robert PicheTampere University of TechnologyVerified email at tuni.fi
Philipp HennigUniversity of Tübingen & Max Planck Institute for Intelligent SystemsVerified email at tue.mpg.de
Juho KokkalaVerified email at aalto.fi
Ali Bahrami RadVisiting Assistant Professor, Emory UniversityVerified email at dbmi.emory.edu
Simo VanniClinical Neurosciences, Neurology; University of Helsinki and Helsinki University HospitalVerified email at helsinki.fi

Simo Särkkä

Associate Professor, Aalto University

Verified email at aalto.fi - Homepage

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


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	2081	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	639	2007
Recursive noise adaptive Kalman filtering by variational Bayesian approximations S Sarkka, A Nummenmaa IEEE Transactions on Automatic control 54 (3), 596-600, 2009	497	2009
Rao-Blackwellized particle filter for multiple target tracking S Sarkka, A Vehtari, J Lampinen Information Fusion 8 (1), 2-15, 2007	356	2007
Unscented rauch--tung--striebel smoother S Särkkä IEEE transactions on automatic control 53 (3), 845-849, 2008	330	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	306*	2008
Applied stochastic differential equations S Särkkä, A Solin Cambridge University Press, 2019	263	2019
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	235	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	198	2013
Recursive Bayesian inference on stochastic differential equations S Särkkä Dissertation Abstracts International, 2006	174	2006
Hilbert space methods for reduced-rank Gaussian process regression A Solin, S Särkkä Statistics and Computing 30 (2), 419-446, 2020	164	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	146	2012
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	139	2012
Rao-Blackwellized Monte Carlo data association for multiple target tracking S Särkkä, A Vehtari, J Lampinen Proceedings of the seventh international conference on information fusion 1 …, 2004	109	2004
On Gaussian optimal smoothing of non-linear state space models S Sarkka, J Hartikainen Automatic Control, IEEE Transactions on 55 (8), 1938-1941, 2010	108	2010
Gaussian filtering and smoothing for continuous-discrete dynamic systems S Särkkä, J Sarmavuori Signal Processing 93 (2), 500-510, 2013	104	2013
Phase-based UHF RFID tracking with nonlinear Kalman filtering and smoothing S Sarkka, VV Viikari, M Huusko, K Jaakkola IEEE Sensors Journal 12 (5), 904-910, 2011	99	2011
Statistical analysis of differential equations: introducing probability measures on numerical solutions PR Conrad, M Girolami, S Särkkä, A Stuart, K Zygalakis Statistics and Computing 27 (4), 1065-1082, 2017	98*	2017
Linear operators and stochastic partial differential equations in Gaussian process regression S Särkkä International Conference on Artificial Neural Networks, 151-158, 2011	95	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	94	2014

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