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
Applied stochastic differential equations
S Särkkä, A Solin
Cambridge University Press, 2019
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
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
Hilbert space methods for reduced-rank Gaussian process regression
A Solin, S Särkkä
Statistics and Computing 30 (2), 419-446, 2020
Recursive Bayesian inference on stochastic differential equations
S Särkkä
Dissertation Abstracts International, 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
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
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
Linear operators and stochastic partial differential equations in Gaussian process regression
S Särkkä
Artificial Neural Networks and Machine Learning–ICANN 2011: 21st …, 2011
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
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
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
Gaussian filtering and smoothing for continuous-discrete dynamic systems
S Särkkä, J Sarmavuori
Signal Processing 93 (2), 500-510, 2013
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