Simo Särkkä integrates Extended Kalman filter and Invariant extended Kalman filter in his studies. He brings together Invariant extended Kalman filter and Unscented transform to produce work in his papers. In his papers, Simo Särkkä integrates diverse fields, such as Unscented transform and Ensemble Kalman filter. He incorporates Ensemble Kalman filter and Kalman filter in his studies. Simo Särkkä applies his multidisciplinary studies on Kalman filter and Fast Kalman filter in his research. While working in this field, Simo Särkkä studies both Fast Kalman filter and Extended Kalman filter. His Pattern recognition (psychology) research extends to Artificial intelligence, which is thematically connected. Much of his study explores Pattern recognition (psychology) relationship to Artificial intelligence. Simo Särkkä merges Algorithm with Applied mathematics in his research.
His work on Statistics as part of general Parametric statistics research is frequently linked to Telecommunications, thereby connecting diverse disciplines of science. Simo Särkkä integrates several fields in his works, including Statistics and Parametric statistics. Simo Särkkä links relevant scientific disciplines such as Iterated function, Discretization, Taylor series and Hermite polynomials in the realm of Mathematical analysis. His research links Mathematical analysis with Discretization. His research on Quantum mechanics often connects related topics like Gaussian. His Gaussian process research extends to the thematically linked field of Gaussian. As part of his studies on Gaussian process, he frequently links adjacent subjects like Quantum mechanics. His Artificial intelligence study frequently draws connections to other fields, such as Particle filter. Simo Särkkä performs multidisciplinary studies into Particle filter and Kalman filter in his work.
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On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems
S. Sarkka.
IEEE Transactions on Automatic Control (2007)
Recursive Noise Adaptive Kalman Filtering by Variational Bayesian Approximations
S. Sarkka;A. Nummenmaa.
IEEE Transactions on Automatic Control (2009)
Rao-Blackwellized particle filter for multiple target tracking
Simo Särkkä;Aki Vehtari;Jouko Lampinen.
Information Fusion (2007)
Unscented Rauch--Tung--Striebel Smoother
S. Sarkka.
IEEE Transactions on Automatic Control (2008)
Kalman filtering and smoothing solutions to temporal Gaussian process regression models
Jouni Hartikainen;Simo Sarkka.
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. Sarkka;A. Solin;J. Hartikainen.
IEEE Signal Processing Magazine (2013)
Recursive Bayesian inference on stochastic differential equations
Simo Särkkä.
(2006)
Applied Stochastic Differential Equations
Simo Särkkä;Arno Solin.
(2019)
Recursive outlier-robust filtering and smoothing for nonlinear systems using the multivariate student-t distribution
Robert Piche;Simo Sarkka;Jouni Hartikainen.
international workshop on machine learning for signal processing (2012)
Dynamic retrospective filtering of physiological noise in BOLD fMRI: DRIFTER
Simo Särkkä;Arno Solin;Aapo Nummenmaa;Aapo Nummenmaa;Aki Vehtari.
NeuroImage (2012)
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