Simo Särkkä

According to our database1, Simo Särkkä authored at least 94 papers between 2000 and 2018.

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2018
Cooperative Localization Using Posterior Linearization Belief Propagation.
IEEE Trans. Vehicular Technology, 2018

Modeling and Interpolation of the Ambient Magnetic Field by Gaussian Processes.
IEEE Trans. Robotics, 2018

Iterative Filtering and Smoothing in Nonlinear and Non-Gaussian Systems Using Conditional Moments.
IEEE Signal Process. Lett., 2018

Fully Symmetric Kernel Quadrature.
SIAM J. Scientific Computing, 2018

Gaussian process classification for prediction of in-hospital mortality among preterm infants.
Neurocomputing, 2018

Inertial-aided Motion Deblurring with Deep Networks.
CoRR, 2018

Gaussian process classification using posterior linearisation.
CoRR, 2018

Probabilistic approach to limited-data computed tomography reconstruction.
CoRR, 2018

Fast Motion Deblurring for Feature Detection and Matching Using Inertial Measurements.
CoRR, 2018

Spectro-Temporal ECG Analysis for atrial fibrillation Detection.
Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

Mixture Representation of the MatéRn class with Applications in State Space Approximations and Bayesian quadrature.
Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

On-Line Bayesian parameter estimation in electrocardiogram State Space Models.
Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

Non-Linear Continuous-Discrete Smoothing by Basis Function Expansions of Brownian Motion.
Proceedings of the 21st International Conference on Information Fusion, 2018

Continuous-Discrete von Mises-Fisher Filtering on S2 for Reference Vector Tracking.
Proceedings of the 21st International Conference on Information Fusion, 2018

Motion Artifact Reduction in Ambulatory Electrocardiography Using Inertial Measurement Units and Kalman Filtering.
Proceedings of the 21st International Conference on Information Fusion, 2018

Tracking of dynamic functional connectivity from MEG data with Kalman filtering.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

2017
Iterated Posterior Linearization Smoother.
IEEE Trans. Automat. Contr., 2017

Statistical analysis of differential equations: introducing probability measures on numerical solutions.
Statistics and Computing, 2017

Gaussian Process Latent Force Models for Learning and Stochastic Control of Physical Systems.
CoRR, 2017

Fully symmetric kernel quadrature.
CoRR, 2017

Detecting malignant ventricular arrhythmias in electrocardiograms by Gaussian process classification.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

A linear stochastic state space model for electrocardiograms.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Classical quadrature rules via Gaussian processes.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Rao-Blackwellized particle mcmc for parameter estimation in spatio-temporal Gaussian processes.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Parallelizable sparse inverse formulation Gaussian processes (SpInGP).
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Inertial-based scale estimation for structure from motion on mobile devices.
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

Student-t process quadratures for filtering of non-linear systems with heavy-tailed noise.
Proceedings of the 20th International Conference on Information Fusion, 2017

RSS-based respiratory rate monitoring using periodic Gaussian processes and Kalman filtering.
Proceedings of the 25th European Signal Processing Conference, 2017

Prediction of preterm infant mortality with Gaussian process classification.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016
Moment conditions for convergence of particle filters with unbounded importance weights.
Signal Processing, 2016

Rao-Blackwellized Particle Smoothers for Conditionally Linear Gaussian Models.
J. Sel. Topics Signal Processing, 2016

A probabilistic model for the numerical solution of initial value problems.
CoRR, 2016

Inertial-Based Scale Estimation for Structure from Motion on Mobile Devices.
CoRR, 2016

On the use of gradient information in Gaussian process quadratures.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Approximate state-space Gaussian processes via spectral transformation.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

IMU and magnetometer modeling for smartphone-based PDR.
Proceedings of the International Conference on Indoor Positioning and Indoor Navigation, 2016

On the LP-convergence of a Girsanov theorem based particle filter.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Sigma-point filtering for nonlinear systems with non-additive heavy-tailed noise.
Proceedings of the 19th International Conference on Information Fusion, 2016

Fourier-Hermite series for stochastic stability analysis of non-linear Kalman filters.
Proceedings of the 19th International Conference on Information Fusion, 2016

Computationally Efficient Bayesian Learning of Gaussian Process State Space Models.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Posterior Linearization Filter: Principles and Implementation Using Sigma Points.
IEEE Trans. Signal Processing, 2015

Gaussian filtering and variational approximations for Bayesian smoothing in continuous-discrete stochastic dynamic systems.
Signal Processing, 2015

Posterior inference on parameters of stochastic differential equations via non-linear Gaussian filtering and adaptive MCMC.
Statistics and Computing, 2015

Combining particle MCMC with Rao-Blackwellized Monte Carlo data association for parameter estimation in multiple target tracking.
Digital Signal Processing, 2015

A Bayesian particle filtering method for brain source localisation.
Digital Signal Processing, 2015

Adaptive Metropolis algorithm using variational Bayesian adaptive Kalman filter.
Computational Statistics & Data Analysis, 2015

Nonlinear State Space Model Identification Using a Regularized Basis Function Expansion.
CoRR, 2015

Modeling and interpolation of the ambient magnetic field by Gaussian processes.
CoRR, 2015

Batch nonlinear continuous-time trajectory estimation as exactly sparse Gaussian process regression.
Auton. Robots, 2015

Adaptive Kalman filtering and smoothing for gravitation tracking in mobile systems.
Proceedings of the 2015 International Conference on Indoor Positioning and Indoor Navigation, 2015

Pedestrian localization in moving platforms using dead reckoning, particle filtering and map matching.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Split-Gaussian particle filter.
Proceedings of the 23rd European Signal Processing Conference, 2015

Nonlinear state space model identification using a regularized basis function expansion.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

State Space Methods for Efficient Inference in Student-t Process Regression.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Series Expansion Approximations of Brownian Motion for Non-Linear Kalman Filtering of Diffusion Processes.
IEEE Trans. Signal Processing, 2014

Batch Nonlinear Continuous-Time Trajectory Estimation as Exactly Sparse Gaussian Process Regression.
CoRR, 2014

Batch Continuous-Time Trajectory Estimation as Exactly Sparse Gaussian Process Regression.
Proceedings of the Robotics: Science and Systems X, 2014

The 10th annual MLSP competition: First place.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Gaussian quadratures for state space approximation of scale mixtures of squared exponential covariance functions.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

On convergence and accuracy of state-space approximations of squared exponential covariance functions.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

On the L4 convergence of particle filters with general importance distributions.
Proceedings of the IEEE International Conference on Acoustics, 2014

Gaussian process quadratures in nonlinear sigma-point filtering and smoothing.
Proceedings of the 17th International Conference on Information Fusion, 2014

Expectation maximization based parameter estimation by sigma-point and particle smoothing.
Proceedings of the 17th International Conference on Information Fusion, 2014

RFID-based butterfly location sensing system.
Proceedings of the 22nd European Signal Processing Conference, 2014

Weight moment conditions for L4 convergence of particle filters for unbounded test functions.
Proceedings of the 22nd European Signal Processing Conference, 2014

Explicit Link Between Periodic Covariance Functions and State Space Models.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Spatiotemporal Learning via Infinite-Dimensional Bayesian Filtering and Smoothing: A Look at Gaussian Process Regression Through Kalman Filtering.
IEEE Signal Process. Mag., 2013

Gaussian filtering and smoothing for continuous-discrete dynamic systems.
Signal Processing, 2013

Continuous-Space Gaussian Process Regression and Generalized Wiener Filtering with Application to Learning Curves.
Proceedings of the Image Analysis, 18th Scandinavian Conference, 2013

Non-linear noise adaptive Kalman filtering via variational Bayes.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2013

Probabilistic initiation and termination for MEG multiple dipole localization using sequential Monte Carlo methods.
Proceedings of the 16th International Conference on Information Fusion, 2013

Bayesian Filtering and Smoothing.
Institute of Mathematical Statistics textbooks 3, Cambridge University Press, ISBN: 978-1-10-761928-9, 2013

2012
Fourier-Hermite Kalman Filter.
IEEE Trans. Automat. Contr., 2012

Dynamic retrospective filtering of physiological noise in BOLD fMRI: DRIFTER.
NeuroImage, 2012

Infinite-Dimensional Kalman Filtering Approach to Spatio-Temporal Gaussian Process Regression.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

State-Space Inference for Non-Linear Latent Force Models with Application to Satellite Orbit Prediction
CoRR, 2012

Sequential Inference for Latent Force Models
CoRR, 2012

The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Recursive outlier-robust filtering and smoothing for nonlinear systems using the multivariate student-t distribution.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

State-Space Inference for Non-Linear Latent Force Models with Application to Satellite Orbit Prediction.
Proceedings of the 29th International Conference on Machine Learning, 2012

Fourier-Hermite Rauch-Tung-Striebel smoother.
Proceedings of the 20th European Signal Processing Conference, 2012

2011
Correction to "On Gaussian Optimal Smoothing of Nonlinear State Space Models" [Aug 10 1938-1941].
IEEE Trans. Automat. Contr., 2011

Sequential Inference for Latent Force Models.
Proceedings of the UAI 2011, 2011

Linear Operators and Stochastic Partial Differential Equations in Gaussian Process Regression.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Learning Curves for Gaussian Processes via Numerical Cubature Integration.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Sparse Spatio-temporal Gaussian Processes with General Likelihoods.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2010
On Gaussian Optimal Smoothing of Non-Linear State Space Models.
IEEE Trans. Automat. Contr., 2010

Continuous-time and continuous-discrete-time unscented Rauch-Tung-Striebel smoothers.
Signal Processing, 2010

2009
Recursive Noise Adaptive Kalman Filtering by Variational Bayesian Approximations.
IEEE Trans. Automat. Contr., 2009

2008
Unscented Rauch-Tung-Striebel Smoother.
IEEE Trans. Automat. Contr., 2008

2007
On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems.
IEEE Trans. Automat. Contr., 2007

Rao-Blackwellized particle filter for multiple target tracking.
Information Fusion, 2007

CATS benchmark time series prediction by Kalman smoother with cross-validated noise density.
Neurocomputing, 2007

2000
On MCMC Sampling in Bayesian MLP Neural Networks.
IJCNN (1), 2000


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