Simo Särkkä

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	All	Since 2016
Citations	6895	4813
h-index	36	32
i10-index	81	71

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Arno SolinAssistant Professor in Machine Learning, Aalto UniversityVerified email at aalto.fi
Aki VehtariAssociate Professor, Aalto UniversityVerified email at aalto.fi
Filip TronarpPostdoctoral researcher, Eberhard Karls University of TübingenVerified email at uni-tuebingen.de
Toni KarvonenResearch Fellow, The Alan Turing InstituteVerified email at turing.ac.uk
Jouko LampinenAalto UniversityVerified email at aalto.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
Lennart SvenssonProfessor in Signal Processing, Chalmers University of TechnologyVerified email at chalmers.se
Isambi Sailon MbalawataUniversity of Dar es SalamVerified email at maths.udsm.ac.tz
Juho KannalaAssistant Professor, Aalto University, FinlandVerified email at aalto.fi
Fa-Hsuan LinSunnybrook Research Institute; University of TorontoVerified email at sri.utoronto.ca
Zheng ZhaoAalto UniversityVerified email at aalto.fi
Thomas SchönProfessor, Uppsala UniversityVerified email at it.uu.se
Simon GodsillUniversity of CambridgeVerified email at eng.cam.ac.uk
Toni AuranenStaff Scientist, Aalto NeuroImaging, Aalto UniversityVerified email at aalto.fi
Robert PicheTampere University of TechnologyVerified email at tuni.fi
Juho KokkalaVerified email at aalto.fi
Andrew M StuartComputing + Mathematical Sciences, CaltechVerified email at caltech.edu
Patrick R. ConradMassachusetts Institute of TechnologyVerified email at mit.edu
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk

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	1518	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	542	2007
Recursive noise adaptive Kalman filtering by variational Bayesian approximations S Sarkka, A Nummenmaa IEEE Transactions on Automatic control 54 (3), 596-600, 2009	379	2009
Rao-Blackwellized particle filter for multiple target tracking S Sarkka, A Vehtari, J Lampinen Information Fusion 8 (1), 2-15, 2007	322	2007
Unscented Rauch--Tung--Striebel Smoother S Särkkä IEEE transactions on automatic control 53 (3), 845-849, 2008	288	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	180	2010
Recursive Bayesian inference on stochastic differential equations S Särkkä Dissertation Abstracts International, 2006	167	2006
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 Process. Mag. 30 (4), 51-61, 2013	166	2013
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	145	2008
Optimal filtering with Kalman filters and smoothers J Hartikainen, A Solin, S Särkkä Department of biomedica engineering and computational sciences, Aalto …, 2011	117*	2011
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	113	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	110	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	107	2004
Applied stochastic differential equations S Särkkä, A Solin Cambridge University Press, 2019	101	2019
On Gaussian optimal smoothing of non-linear state space models S Sarkka, J Hartikainen Automatic Control, IEEE Transactions on 55 (8), 1938-1941, 2010	94	2010
Hilbert space methods for reduced-rank Gaussian process regression A Solin, S Särkkä Statistics and Computing 30 (2), 419-446, 2020	88	2020
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	85	2011
Gaussian filtering and smoothing for continuous-discrete dynamic systems S Särkkä, J Sarmavuori Signal Processing 93 (2), 500-510, 2013	83	2013
Fourier-hermite kalman filter J Sarmavuori, S Sarkka IEEE Transactions on Automatic Control 57 (6), 1511-1515, 2011	73	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	71*	2017

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