Simo Särkkä
Cited by
Cited by
Bayesian filtering and smoothing
S Särkkä
Cambridge University Press, 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
Recursive noise adaptive Kalman filtering by variational Bayesian approximations
S Sarkka, A Nummenmaa
IEEE Transactions on Automatic control 54 (3), 596-600, 2009
Rao-Blackwellized particle filter for multiple target tracking
S Sarkka, A Vehtari, J Lampinen
Information Fusion 8 (1), 2-15, 2007
Unscented rauch--tung--striebel smoother
S Särkkä
IEEE transactions on automatic control 53 (3), 845-849, 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
Applied stochastic differential equations
S Särkkä, A Solin
Cambridge University Press, 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
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
Recursive Bayesian inference on stochastic differential equations
S Särkkä
Dissertation Abstracts International, 2006
Hilbert space methods for reduced-rank Gaussian process regression
A Solin, S Särkkä
Statistics and Computing 30 (2), 419-446, 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
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
On Gaussian optimal smoothing of non-linear state space models
S Sarkka, J Hartikainen
Automatic Control, IEEE Transactions on 55 (8), 1938-1941, 2010
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
Gaussian filtering and smoothing for continuous-discrete dynamic systems
S Särkkä, J Sarmavuori
Signal Processing 93 (2), 500-510, 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
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
Linear operators and stochastic partial differential equations in Gaussian process regression
S Särkkä
International Conference on Artificial Neural Networks, 151-158, 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
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