On MCMC Sampling in Bayesian MLP Neural Networks. - Aki Vehtari; Simo Särkkä; Jouko Lampinen (IJCNN (1), 2000)

Time series prediction by Kalman smoother with cross-validated noise density. - Simo Särkkä; Aki Vehtari; Jouko Lampinen (IJCNN, 2004)

CATS benchmark time series prediction by Kalman smoother with cross-validated noise density. - Simo Särkkä; Aki Vehtari; Jouko Lampinen (Neurocomputing, 2007)

Rao-Blackwellized particle filter for multiple target tracking. - Simo Särkkä; Aki Vehtari; Jouko Lampinen (Inf. Fusion, 2007)

On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems. - Simo Särkkä (IEEE Trans. Autom. Control., 2007)

Unscented Rauch-Tung-Striebel Smoother. - Simo Särkkä (IEEE Trans. Autom. Control., 2008)

Recursive Noise Adaptive Kalman Filtering by Variational Bayesian Approximations. - Simo Särkkä; Aapo Nummenmaa (IEEE Trans. Autom. Control., 2009)

Continuous-time and continuous-discrete-time unscented Rauch-Tung-Striebel smoothers. - Simo Särkkä (Signal Process., 2010)

On Gaussian Optimal Smoothing of Non-Linear State Space Models. - Simo Särkkä; Jouni Hartikainen (IEEE Trans. Autom. Control., 2010)

Sparse Spatio-temporal Gaussian Processes with General Likelihoods. - Jouni Hartikainen; Jaakko Riihimäki; Simo Särkkä (ICANN (1), 2011)

Learning Curves for Gaussian Processes via Numerical Cubature Integration. - Simo Särkkä (ICANN (1), 2011)

Linear Operators and Stochastic Partial Differential Equations in Gaussian Process Regression. - Simo Särkkä (ICANN (2), 2011)

Sequential Inference for Latent Force Models. - Jouni Hartikainen; Simo Särkkä (UAI, 2011)

Correction to "On Gaussian Optimal Smoothing of Nonlinear State Space Models" [Aug 10 1938-1941]. - Simo Särkkä; Jouni Hartikainen (IEEE Trans. Autom. Control., 2011)

Accurate Discretization of Analog Audio Filters With Application to Parametric Equalizer Design. - Simo Särkkä; Antti Huovilainen (IEEE ACM Trans. Audio Speech Lang. Process., 2011)

Fourier-Hermite Rauch-Tung-Striebel smoother. - Juha Sarmavuori; Simo Särkkä (EUSIPCO, 2012)

State-Space Inference for Non-Linear Latent Force Models with Application to Satellite Orbit Prediction. - Jouni Hartikainen; Mari Seppänen; Simo Särkkä (ICML, 2012)

Recursive outlier-robust filtering and smoothing for nonlinear systems using the multivariate student-t distribution. - Robert Piché; Simo Särkkä; Jouni Hartikainen (MLSP, 2012)

The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes. - Simon M. J. Lyons; Amos J. Storkey; Simo Särkkä (NIPS, 2012)

Infinite-Dimensional Kalman Filtering Approach to Spatio-Temporal Gaussian Process Regression. - Simo Särkkä; Jouni Hartikainen (AISTATS, 2012)

Dynamic retrospective filtering of physiological noise in BOLD fMRI: DRIFTER. - Simo Särkkä; Arno Solin; Aapo Nummenmaa; Aki Vehtari; Toni Auranen; Simo Vanni; Fa-Hsuan Lin (NeuroImage, 2012)

Fourier-Hermite Kalman Filter. - Juha Sarmavuori; Simo Särkkä (IEEE Trans. Autom. Control., 2012)

Bayesian Filtering and Smoothing. - Simo Särkkä (Cambridge University Press, 2013)

Probabilistic initiation and termination for MEG multiple dipole localization using sequential Monte Carlo methods. - Xi Chen 042; Simo Särkkä; Simon J. Godsill (FUSION, 2013)

Non-linear noise adaptive Kalman filtering via variational Bayes. - Simo Särkkä; Jouni Hartikainen (MLSP, 2013)

Continuous-Space Gaussian Process Regression and Generalized Wiener Filtering with Application to Learning Curves. - Simo Särkkä; Arno Solin (SCIA, 2013)

Parameter estimation in stochastic differential equations with Markov chain Monte Carlo and non-linear Kalman filtering. - Isambi S. Mbalawata; Simo Särkkä; Heikki Haario (Comput. Stat., 2013)

Gaussian filtering and smoothing for continuous-discrete dynamic systems. - Simo Särkkä; Juha Sarmavuori (Signal Process., 2013)

Spatiotemporal Learning via Infinite-Dimensional Bayesian Filtering and Smoothing: A Look at Gaussian Process Regression Through Kalman Filtering. - Simo Särkkä; Arno Solin; Jouni Hartikainen (IEEE Signal Process. Mag., 2013)

Explicit Link Between Periodic Covariance Functions and State Space Models. - Arno Solin; Simo Särkkä (AISTATS, 2014)

Weight moment conditions for L4 convergence of particle filters for unbounded test functions. - Isambi S. Mbalawata; Simo Särkkä (EUSIPCO, 2014)

RFID-based butterfly location sensing system. - Simo Särkkä; Ville Viikari; Kaarle Jaakkola (EUSIPCO, 2014)

Expectation maximization based parameter estimation by sigma-point and particle smoothing. - Juho Kokkala; Arno Solin; Simo Särkkä (FUSION, 2014)

Gaussian process quadratures in nonlinear sigma-point filtering and smoothing. - Simo Särkkä; Jouni Hartikainen; Lennart Svensson; Fredrik Sandblom (FUSION, 2014)

On the L4 convergence of particle filters with general importance distributions. - Isambi S. Mbalawata; Simo Särkkä (ICASSP, 2014)

On convergence and accuracy of state-space approximations of squared exponential covariance functions. - Simo Särkkä; Robert Piché (MLSP, 2014)

Gaussian quadratures for state space approximation of scale mixtures of squared exponential covariance functions. - Arno Solin; Simo Särkkä (MLSP, 2014)

The 10th annual MLSP competition: First place. - Arno Solin; Simo Särkkä (MLSP, 2014)

Batch Continuous-Time Trajectory Estimation as Exactly Sparse Gaussian Process Regression. - Tim D. Barfoot; Chi Hay Tong; Simo Särkkä (Robotics: Science and Systems, 2014)

Series Expansion Approximations of Brownian Motion for Non-Linear Kalman Filtering of Diffusion Processes. - Simon M. J. Lyons; Simo Särkkä; Amos J. Storkey (IEEE Trans. Signal Process., 2014)

State Space Methods for Efficient Inference in Student-t Process Regression. - Arno Solin; Simo Särkkä (AISTATS, 2015)

Nonlinear state space model identification using a regularized basis function expansion. - Andreas Svensson; Thomas B. Schön; Arno Solin; Simo Särkkä (CAMSAP, 2015)

Split-Gaussian particle filter. - Juho Kokkala; Simo Särkkä (EUSIPCO, 2015)

Pedestrian localization in moving platforms using dead reckoning, particle filtering and map matching. - Jayaprasad Bojja; Jussi Collin; Simo Särkkä; Jarmo Takala (ICASSP, 2015)

Adaptive Kalman filtering and smoothing for gravitation tracking in mobile systems. - Simo Särkkä; Ville Tolvanen; Juho Kannala; Esa Rahtu (IPIN, 2015)

Batch nonlinear continuous-time trajectory estimation as exactly sparse Gaussian process regression. - Sean Anderson; Timothy D. Barfoot; Chi Hay Tong; Simo Särkkä (Auton. Robots, 2015)

Adaptive Metropolis algorithm using variational Bayesian adaptive Kalman filter. - Isambi S. Mbalawata; Simo Särkkä; Matti Vihola; Heikki Haario (Comput. Stat. Data Anal., 2015)

A Bayesian particle filtering method for brain source localisation. - Xi Chen 042; Simo Särkkä; Simon J. Godsill (Digit. Signal Process., 2015)

Combining particle MCMC with Rao-Blackwellized Monte Carlo data association for parameter estimation in multiple target tracking. - Juho Kokkala; Simo Särkkä (Digit. Signal Process., 2015)

Posterior inference on parameters of stochastic differential equations via non-linear Gaussian filtering and adaptive MCMC. - Simo Särkkä; Jouni Hartikainen; Isambi Sailon Mbalawata; Heikki Haario (Stat. Comput., 2015)

Gaussian filtering and variational approximations for Bayesian smoothing in continuous-discrete stochastic dynamic systems. - Juha Ala-Luhtala; Simo Särkkä; Robert Piché (Signal Process., 2015)

Posterior Linearization Filter: Principles and Implementation Using Sigma Points. - Ángel F. García-Fernández; Lennart Svensson; Mark R. Morelande; Simo Särkkä (IEEE Trans. Signal Process., 2015)

Computationally Efficient Bayesian Learning of Gaussian Process State Space Models. - Andreas Svensson; Arno Solin; Simo Särkkä; Thomas B. Schön (AISTATS, 2016)

Fourier-Hermite series for stochastic stability analysis of non-linear Kalman filters. - Toni Karvonen; Simo Särkkä (FUSION, 2016)

Sigma-point filtering for nonlinear systems with non-additive heavy-tailed noise. - Filip Tronarp; Roland Hostettler; Simo Särkkä (FUSION, 2016)

On the LP-convergence of a Girsanov theorem based particle filter. - Simo Särkkä; Eric Moulines (ICASSP, 2016)

IMU and magnetometer modeling for smartphone-based PDR. - Roland Hostettler; Simo Särkkä (IPIN, 2016)

Approximate state-space Gaussian processes via spectral transformation. - Toni Karvonen; Simo Särkkä (MLSP, 2016)

On the use of gradient information in Gaussian process quadratures. - Jakub Prüher; Simo Särkkä (MLSP, 2016)

Rao-Blackwellized Particle Smoothers for Conditionally Linear Gaussian Models. - Fredrik Lindsten; Pete Bunch; Simo Särkkä; Thomas B. Schön; Simon J. Godsill (IEEE J. Sel. Top. Signal Process., 2016)

Moment conditions for convergence of particle filters with unbounded importance weights. - Isambi S. Mbalawata; Simo Särkkä (Signal Process., 2016)

Prediction of preterm infant mortality with Gaussian process classification. - Olli-Pekka Rinta-Koski; Simo Särkkä; Jaakko Hollmén; Markus Leskinen; Sture Andersson (ESANN, 2017)

RSS-based respiratory rate monitoring using periodic Gaussian processes and Kalman filtering. - Roland Hostettler; Ossi Kaltiokallio; Hüseyin Yigitler; Simo Särkkä; Riku Jäntti (EUSIPCO, 2017)

Student-t process quadratures for filtering of non-linear systems with heavy-tailed noise. - Jakub Prüher; Filip Tronarp; Toni Karvonen; Simo Särkkä; Ondrej Straka (FUSION, 2017)

Inertial-based scale estimation for structure from motion on mobile devices. - Janne Mustaniemi; Juho Kannala; Simo Särkkä; Jiri Matas; Janne Heikkilä (IROS, 2017)

Parallelizable sparse inverse formulation Gaussian processes (SpInGP). - Alexander Grigorievskiy; Neil D. Lawrence; Simo Särkkä (MLSP, 2017)

Rao-Blackwellized particle mcmc for parameter estimation in spatio-temporal Gaussian processes. - Roland Hostettler; Simo Särkkä; Simon J. Godsill (MLSP, 2017)

Classical quadrature rules via Gaussian processes. - Toni Karvonen; Simo Särkkä (MLSP, 2017)

A linear stochastic state space model for electrocardiograms. - Kimmo Suotsalo; Simo Särkkä (MLSP, 2017)

Detecting malignant ventricular arrhythmias in electrocardiograms by Gaussian process classification. - Kimmo Suotsalo; Simo Särkkä (MLSP, 2017)

Statistical analysis of differential equations: introducing probability measures on numerical solutions. - Patrick R. Conrad; Mark A. Girolami; Simo Särkkä; Andrew M. Stuart; Konstantinos Zygalakis (Stat. Comput., 2017)

Iterated Posterior Linearization Smoother. - Ángel F. García-Fernández; Lennart Svensson; Simo Särkkä (IEEE Trans. Autom. Control., 2017)

Bounds on the Covariance Matrix of a Class of Kalman-Bucy Filters for Systems with Non-Linear Dynamics. - Toni Karvonen; Silvère Bonnabel; Eric Moulines; Simo Särkkä (CDC, 2018)

Automatic Sleep Arousal Detection Using Multimodal Biosignal Analysis. - Morteza Zabihi; Ali Bahrami Rad; Simo Särkkä; Serkan Kiranyaz; Aggelos K. Katsaggelos; Moncef Gabbouj (CinC, 2018)

Tracking of dynamic functional connectivity from MEG data with Kalman filtering. - Filip Tronarp; Narayan Puthanmadam Subramaniyam; Simo Särkkä; Lauri Parkkonen (EMBC, 2018)

Combined Analysis-L1 and Total Variation ADMM with Applications to MEG Brain Imaging and Signal Reconstruction. - Rui Gao; Filip Tronarp; Simo Särkkä (EUSIPCO, 2018)

Motion Artifact Reduction in Ambulatory Electrocardiography Using Inertial Measurement Units and Kalman Filtering. - Roland Hostettler; Tuomas Lumikari; Lauri Palva; Tuomo Nieminen; Simo Särkkä (FUSION, 2018)

Continuous-Discrete von Mises-Fisher Filtering on S2 for Reference Vector Tracking. - Filip Tronarp; Roland Hostettler; Simo Särkkä (FUSION, 2018)

Non-Linear Continuous-Discrete Smoothing by Basis Function Expansions of Brownian Motion. - Filip Tronarp; Simo Särkkä (FUSION, 2018)

Fast Motion Deblurring for Feature Detection and Matching Using Inertial Measurements. - Janne Mustaniemi; Juho Kannala; Simo Särkkä; Jiri Matas; Janne Heikkilä (ICPR, 2018)

On-Line Bayesian parameter estimation in electrocardiogram State Space Models. - Kimmo Suotsalo; Simo Särkkä (MLSP, 2018)

Mixture Representation of the MatéRn class with Applications in State Space Approximations and Bayesian quadrature. - Filip Tronarp; Toni Karvonen; Simo Särkkä (MLSP, 2018)

Spectro-Temporal ECG Analysis for atrial fibrillation Detection. - Zheng Zhao 004; Simo Särkkä; Ali Bahrami Rad (MLSP, 2018)

A Bayes-Sard Cubature Method. - Toni Karvonen; Chris J. Oates; Simo Särkkä (NeurIPS, 2018)

Probabilistic approach to limited-data computed tomography reconstruction. - Zenith Purisha; Carl Jidling; Niklas Wahlström; Simo Särkkä; Thomas B. Schön (CoRR, 2018)

Gaussian process classification using posterior linearisation. - Ángel F. García-Fernández; Filip Tronarp; Simo Särkkä (CoRR, 2018)

Inertial-aided Motion Deblurring with Deep Networks. - Janne Mustaniemi; Juho Kannala; Simo Särkkä; Jiri Matas; Janne Heikkilä (CoRR, 2018)

LSD2 - Joint Denoising and Deblurring of Short and Long Exposure Images with Convolutional Neural Networks. - Janne Mustaniemi; Juho Kannala; Jiri Matas; Simo Särkkä; Janne Heikkilä (CoRR, 2018)

Gaussian process classification for prediction of in-hospital mortality among preterm infants. - Olli-Pekka Rinta-Koski; Simo Särkkä; Jaakko Hollmén; Markus Leskinen; Sture Andersson (Neurocomputing, 2018)

Fully Symmetric Kernel Quadrature. - Toni Karvonen; Simo Särkkä (SIAM J. Sci. Comput., 2018)

Iterative Filtering and Smoothing in Nonlinear and Non-Gaussian Systems Using Conditional Moments. - Filip Tronarp; Ángel F. García-Fernández; Simo Särkkä (IEEE Signal Process. Lett., 2018)

Modeling and Interpolation of the Ambient Magnetic Field by Gaussian Processes. - Arno Solin; Manon Kok; Niklas Wahlstrom; Thomas B. Schön; Simo Särkkä (IEEE Trans. Robotics, 2018)

Cooperative Localization Using Posterior Linearization Belief Propagation. - Ángel F. García-Fernández; Lennart Svensson; Simo Särkkä (IEEE Trans. Veh. Technol., 2018)

Joint Calibration of Inertial Sensors and Magnetometers using von Mises-Fisher Filtering and Expectation Maximization. - Roland Hostettler; Ángel F. García-Fernández; Filip Tronarp; Simo Särkkä (FUSION, 2019)

Partitioned Update Binomial Gaussian Mixture Filter. - Matti Raitoharju; Ángel F. García-Fernández; Simo Särkkä (FUSION, 2019)

Updates in Bayesian Filtering by Continuous Projections on a Manifold of Densities. - Filip Tronarp; Simo Särkkä (ICASSP, 2019)

Hilbert-Space Reduced-Rank Methods For Deep Gaussian Processes. - Muhammad F. Emzir; Sari Lasanen; Zenith Purisha; Simo Särkkä (MLSP, 2019)

Regularized State Estimation And Parameter Learning Via Augmented Lagrangian Kalman Smoother Method. - Rui Gao; Filip Tronarp; Zheng Zhao 004; Simo Särkkä (MLSP, 2019)

Rejection-Sampling-Based Ancestor Sampling for Particle Gibbs. - Roland Hostettler; Simo Särkkä (MLSP, 2019)

Asymptotics of Maximum Likelihood Parameter Estimates For Gaussian Processes: The Ornstein-Uhlenbeck Prior. - Toni Karvonen; Filip Tronarp; Simo Särkkä (MLSP, 2019)

Gyroscope-Aided Motion Deblurring with Deep Networks. - Janne Mustaniemi; Juho Kannala; Simo Särkkä; Jiri Matas; Janne Heikkilä (WACV, 2019)

1D Convolutional Neural Network Models for Sleep Arousal Detection. - Morteza Zabihi; Ali Bahrami Rad; Serkan Kiranyaz; Simo Särkkä; Moncef Gabbouj (CoRR, 2019)

Temporal Parallelization of Bayesian Filters and Smoothers. - Simo Särkkä; Ángel F. García-Fernández (CoRR, 2019)

The Use of Gaussian Processes in System Identification. - Simo Särkkä (CoRR, 2019)

Automated Polysomnography Analysis for Detection of Non-Apneic and Non-Hypopneic Arousals using Feature Engineering and a Bidirectional LSTM Network. - Ali Bahrami Rad; Morteza Zabihi; Zheng Zhao 004; Moncef Gabbouj; Aggelos K. Katsaggelos; Simo Särkkä (CoRR, 2019)

On the Convergence of Numerical Integration as a Finite Matrix Approximation to Multiplication Operator. - Juha Sarmavuori; Simo Särkkä (CoRR, 2019)

Numerical integration as a finite matrix approximation to multiplication operator. - Juha Sarmavuori; Simo Särkkä (J. Comput. Appl. Math., 2019)

On the positivity and magnitudes of Bayesian quadrature weights. - Toni Karvonen; Motonobu Kanagawa; Simo Särkkä (Stat. Comput., 2019)

Symmetry exploits for Bayesian cubature methods. - Toni Karvonen; Simo Särkkä; Chris J. Oates (Stat. Comput., 2019)

A probabilistic model for the numerical solution of initial value problems. - Michael Schober; Simo Särkkä; Philipp Hennig (Stat. Comput., 2019)

Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective. - Filip Tronarp; Hans Kersting; Simo Särkkä; Philipp Hennig (Stat. Comput., 2019)

Iterative statistical linear regression for Gaussian smoothing in continuous-time non-linear stochastic dynamic systems. - Filip Tronarp; Simo Särkkä (Signal Process., 2019)

Gaussian Process Classification Using Posterior Linearization. - Ángel F. García-Fernández; Filip Tronarp; Simo Särkkä (IEEE Signal Process. Lett., 2019)

Student's $t$-Filters for Noise Scale Estimation. - Filip Tronarp; Toni Karvonen; Simo Särkkä (IEEE Signal Process. Lett., 2019)

Rao-Blackwellized Gaussian Smoothing. - Roland Hostettler; Simo Särkkä (IEEE Trans. Autom. Control., 2019)

Gaussian Process Latent Force Models for Learning and Stochastic Control of Physical Systems. - Simo Särkkä; Mauricio A. Álvarez; Neil D. Lawrence (IEEE Trans. Autom. Control., 2019)

Iterated Extended Kalman Smoother-Based Variable Splitting for L1-Regularized State Estimation. - Rui Gao; Filip Tronarp; Simo Särkkä (IEEE Trans. Signal Process., 2019)

Gaussian Target Tracking With Direction-of-Arrival von Mises-Fisher Measurements. - Ángel F. García-Fernández; Filip Tronarp; Simo Särkkä (IEEE Trans. Signal Process., 2019)

Rao-Blackwellized Posterior Linearization Backward SLAM. - Ángel F. García-Fernández; Roland Hostettler; Simo Särkkä (IEEE Trans. Veh. Technol., 2019)

LSD_2 - Joint Denoising and Deblurring of Short and Long Exposure Images with CNNs. - Janne Mustaniemi; Juho Kannala; Jiri Matas; Simo Särkkä; Janne Heikkilä (BMVC, 2020)

Respiratory Pattern Recognition from Low-Resolution Thermal Imaging. - Salla Aario; Ajinkya Gorad; Miika Arvonen; Simo Särkkä (ESANN, 2020)

Augmented Sigma-Point Lagrangian Splitting Method for Sparse Nonlinear State Estimation. - Rui Gao; Simo Särkkä (EUSIPCO, 2020)

Levenberg-Marquardt and Line-Search Extended Kalman Smoothers. - Simo Särkkä; Lennart Svensson (ICASSP, 2020)

State-Space Gaussian Process for Drift Estimation in Stochastic Differential Equations. - Zheng Zhao 004; Filip Tronarp; Roland Hostettler; Simo Särkkä (ICASSP, 2020)

Parameter Estimation in Non-Linear State-Space Models by Automatic Differentiation of Non-Linear Kalman Filters. - Ajinkya Gorad; Zheng Zhao 004; Simo Särkkä (MLSP, 2020)

Machine Learning Methods for Neonatal Mortality and Morbidity Classification. - Joel Jaskari; Janne Myllärinen; Markus Leskinen; Ali Bahrami Rad; Jaakko Hollmén; Sture Andersson; Simo Särkkä (IEEE Access, 2020)

Worst-case optimal approximation with increasingly flat Gaussian kernels. - Toni Karvonen; Simo Särkkä (Adv. Comput. Math., 2020)

Enhancing Industrial X-ray Tomography by Data-Centric Statistical Methods. - Jarkko Suuronen; Muhammad F. Emzir; Sari Lasanen; Simo Särkkä; Lassi Roininen (CoRR, 2020)

A survey of Monte Carlo methods for parameter estimation. - David Luengo; Luca Martino; Mónica F. Bugallo; Víctor Elvira; Simo Särkkä (EURASIP J. Adv. Signal Process., 2020)

Maximum Likelihood Estimation and Uncertainty Quantification for Gaussian Process Approximation of Deterministic Functions. - Toni Karvonen; George Wynne; Filip Tronarp; Chris J. Oates; Simo Särkkä (SIAM/ASA J. Uncertain. Quantification, 2020)

Hilbert space methods for reduced-rank Gaussian process regression. - Arno Solin; Simo Särkkä (Stat. Comput., 2020)

On Stability of a Class of Filters for Nonlinear Stochastic Systems. - Toni Karvonen; Silvère Bonnabel; Eric Moulines; Simo Särkkä (SIAM J. Control. Optim., 2020)

Gaussian mixture models for signal mapping and positioning. - Matti Raitoharju; Ángel F. García-Fernández; Roland Hostettler; Robert Piché; Simo Särkkä (Signal Process., 2020)

Variable Splitting Methods for Constrained State Estimation in Partially Observed Markov Processes. - Rui Gao; Filip Tronarp; Simo Särkkä (IEEE Signal Process. Lett., 2020)

Importance Densities for Particle Filtering Using Iterated Conditional Expectations. - Roland Hostettler; Filip Tronarp; Ángel F. García-Fernández; Simo Särkkä (IEEE Signal Process. Lett., 2020)

RSS Models for Respiration Rate Monitoring. - Hüseyin Yigitler; Ossi Kaltiokallio; Roland Hostettler; Alemayehu Solomon Abrar; Riku Jäntti; Neal Patwari; Simo Särkkä (IEEE Trans. Mob. Comput., 2020)

Kalman-based Spectro-Temporal ECG Analysis using Deep Convolutional Networks for Atrial Fibrillation Detection. - Zheng Zhao 004; Simo Särkkä; Ali Bahrami Rad (J. Signal Process. Syst., 2020)

Real-Time Tracking of Multiple Acoustical Sources Utilising Rao-Blackwellised Particle Filtering. - Leo McCormack; Archontis Politis; Simo Särkkä; Ville Pulkki (EUSIPCO, 2021)

Parallel Iterated Extended and Sigma-Point Kalman Smoothers. - Fatemeh Yaghoobi; Adrien Corenflos; Sakira Hassan; Simo Särkkä (ICASSP, 2021)

Kalman filtering with empirical noise models. - Matti Raitoharju; Henri Nurminen; Demet Cilden-Guler; Simo Särkkä (ICL-GNSS, 2021)

Metal Artifact Reduction In Cone-Beam Extremity Images Using Gated Convolutions. - Harshit Agrawal; Ari Hietanen; Simo Särkkä (ISBI, 2021)

Gaussian Approximations of SDES in Metropolis-Adjusted Langevin Algorithms. - Simo Särkkä; Christos Merkatas; Toni Karvonen (MLSP, 2021)

A Probabilistic Taylor Expansion with Applications in Filtering and Differential Equations. - Toni Karvonen; Jon Cockayne; Filip Tronarp; Simo Särkkä (CoRR, 2021)

Gaussian Process Regression in Logarithmic Time. - Adrien Corenflos; Zheng Zhao 004; Simo Särkkä (CoRR, 2021)

Temporal Parallelisation of Dynamic Programming and Linear Quadratic Control. - Simo Särkkä; Ángel F. García-Fernández (CoRR, 2021)

Kernel-based interpolation at approximate Fekete points. - Toni Karvonen; Simo Särkkä; Ken'ichiro Tanaka (Numer. Algorithms, 2021)

Correction to: Kernel-based interpolation at approximate Fekete points. - Toni Karvonen; Simo Särkkä; Ken'ichiro Tanaka (Numer. Algorithms, 2021)

Bayesian ODE solvers: the maximum a posteriori estimate. - Filip Tronarp; Simo Särkkä; Philipp Hennig (Stat. Comput., 2021)

Deep state-space Gaussian processes. - Zheng Zhao 004; Muhammad F. Emzir; Simo Särkkä (Stat. Comput., 2021)

Improved Calibration of Numerical Integration Error in Sigma-Point Filters. - Jakub Prüher; Toni Karvonen; Chris J. Oates; Ondrej Straka; Simo Särkkä (IEEE Trans. Autom. Control., 2021)

Temporal Parallelization of Bayesian Smoothers. - Simo Särkkä; Ángel F. García-Fernández (IEEE Trans. Autom. Control., 2021)

Taylor Moment Expansion for Continuous-Discrete Gaussian Filtering. - Zheng Zhao 004; Toni Karvonen; Roland Hostettler; Simo Särkkä (IEEE Trans. Autom. Control., 2021)

Temporal Parallelization of Inference in Hidden Markov Models. - Syeda Sakira Hassan; Simo Särkkä; Ángel F. García-Fernández (IEEE Trans. Signal Process., 2021)

Temporal Gaussian Process Regression in Logarithmic Time. - Adrien Corenflos; Zheng Zhao 004; Simo Särkkä (FUSION, 2022)

Fast optimize-and-sample method for differentiable Galerkin approximations of multi-layered Gaussian process priors. - Muhammad F. Emzir; Niki Andreas Lopi; Zheng Zhao 004; Syeda Sakira Hassan; Simo Särkkä (FUSION, 2022)

Posterior linearisation filter for non-linear state transformation noises. - Matti Raitoharju; Roland Hostettler; Simo Särkkä (FUSION, 2022)

Continuous-Discrete Filtering and Smoothing on Submanifolds of Euclidean Space. - Filip Tronarp; Simo Särkkä (FUSION, 2022)

Uncertainty-Aware Deep Learning Methods for Robust Diabetic Retinopathy Classification. - Joel Jaskari; Jaakko Sahlsten; Theodoros Damoulas; Jeremias Knoblauch; Simo Särkkä; Leo Kärkkäinen; Kustaa Hietala; Kimmo K. Kaski (IEEE Access, 2022)

Metal artifact correction in cone beam computed tomography using synthetic X-ray data. - Harshit Agrawal; Ari Hietanen; Simo Särkkä (CoRR, 2022)

Temporal Parallelisation of the HJB Equation and Continuous-Time Linear Quadratic Control. - Simo Särkkä; Ángel F. García-Fernández (CoRR, 2022)

De-Sequentialized Monte Carlo: a parallel-in-time particle smoother. - Adrien Corenflos; Nicolas Chopin; Simo Särkkä (J. Mach. Learn. Res., 2022)

Non-Linear Gaussian Smoothing With Taylor Moment Expansion. - Zheng Zhao 004; Simo Särkkä (IEEE Signal Process. Lett., 2022)

Autonomous Tracking and State Estimation With Generalized Group Lasso. - Rui Gao; Simo Särkkä; Rubén M. Clavería; Simon J. Godsill (IEEE Trans. Cybern., 2022)

Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review. - Sarang Thombre; Zheng Zhao 004; Henrik Ramm-Schmidt; José M. Vallet Garcia; Tuomo Malkamäki; Sergey Nikolskiy; Toni Hammarberg; Hiski Nuortie; Mohammad Zahidul H. Bhuiyan; Simo Särkkä; Ville V. Lehtola (IEEE Trans. Intell. Transp. Syst., 2022)

Guest Editorial: MLSP 2020 Special Issue. - Simo Särkkä; Lassi Roininen; Manon Kok; Roland Hostettler; Andreas Hauptmann (J. Signal Process. Syst., 2022)

On The Temporal Parallelisation of The Viterbi Algorithm. - Simo Särkkä; Ángel F. García-Fernández (EUSIPCO, 2023)

A Recursive Newton Method for Smoothing in Nonlinear State Space Models. - Fatemeh Yaghoobi; Hany Abdulsamad; Simo Särkkä (EUSIPCO, 2023)

Indoor Positioning Methods Based on Dual Feet-Mounted IMUs With Distance Constraints. - Xiaofeng Ma; Simo Särkkä (IPIN, 2023)

Nonparametric modeling of the composite effect of multiple nutrients on blood glucose dynamics. - Arina Odnoblyudova; Caglar Hizli; St John; Andrea Cognolato; Anne Juuti; Simo Särkkä; Kirsi Pietiläinen; Pekka Marttinen (ML4H@NeurIPS, 2023)

Rao-Blackwellized Monte Carlo Data Association With Deep Metric For Object Tracking. - Ajinkya Gorad; Simo Särkkä (MLSP, 2023)

Single Qubit State Estimation on NISQ Devices with Limited Resources and SIC-POVMs. - Cristian A. Galvis-Florez; Daniel Reitzner; Simo Särkkä (QCE, 2023)

Vessel Bearing Estimation Using Visible and Thermal Imaging. - Ajinkya Gorad; Sakira Hassan; Simo Särkkä (SCIA (2), 2023)

Fast Dynamic Programming in Trees in the MPC Model. - Chetan Gupta 002; Rustam Latypov; Yannic Maus; Shreyas Pai; Simo Särkkä; Jan Studený; Jukka Suomela; Jara Uitto; Hossein Vahidi 001 (SPAA, 2023)

Deep Learning Based Projection Domain Metal Segmentation for Metal Artifact Reduction in Cone Beam Computed Tomography. - Harshit Agrawal; Ari Hietanen; Simo Särkkä (IEEE Access, 2023)

Auxiliary MCMC and particle Gibbs samplers for parallelisable inference in latent dynamical systems. - Adrien Corenflos; Simo Särkkä (CoRR, 2023)

Risk-Sensitive Stochastic Optimal Control as Rao-Blackwellized Markovian Score Climbing. - Hany Abdulsamad; Sahel Iqbal; Adrien Corenflos; Simo Särkkä (CoRR, 2023)

Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees. - William J. Wilkinson; Simo Särkkä; Arno Solin (J. Mach. Learn. Res., 2023)

Online pole segmentation on range images for long-term LiDAR localization in urban environments. - Hao Dong 011; Xieyuanli Chen; Simo Särkkä; Cyrill Stachniss (Robotics Auton. Syst., 2023)

Multidimensional projection filters via automatic differentiation and sparse-grid integration. - Muhammad F. Emzir; Zheng Zhao 004; Simo Särkkä (Signal Process., 2023)

A probabilistic Taylor expansion with Gaussian processes. - Toni Karvonen; Jon Cockayne; Filip Tronarp; Simo Särkkä (Trans. Mach. Learn. Res., 2023)

Probabilistic Estimation of Instantaneous Frequencies of Chirp Signals. - Zheng Zhao 004; Simo Särkkä; Jens Sjölund; Thomas B. Schön (IEEE Trans. Signal Process., 2023)

Temporal Parallelization of Dynamic Programming and Linear Quadratic Control. - Simo Särkkä; Ángel F. García-Fernández (IEEE Trans. Autom. Control., 2023)

Fourier-Hermite Dynamic Programming for Optimal Control. - Syeda Sakira Hassan; Simo Särkkä (IEEE Trans. Autom. Control., 2023)

Polynomial Chaos Expansion Based Rauch-Tung-Striebel Smoothers. - Kundan Kumar; Simo Särkkä (FUSION, 2024)

Stacked iterated posterior linearization filter. - Matti Raitoharju; Ángel F. García-Fernández; Simo Ali-Löytty; Simo Särkkä (FUSION, 2024)

A Gibbs Sampler for Bayesian Nonparametric State-Space Models. - Christos Merkatas; Simo Särkkä (ICASSP, 2024)

Nesting Particle Filters for Experimental Design in Dynamical Systems. - Sahel Iqbal; Adrien Corenflos; Simo Särkkä; Hany Abdulsamad (ICML, 2024)

Risk-Sensitive Filtering under False Data Injection Attacks. - Kundan Kumar; Muhammad Iqbal; Simo Särkkä (MFI, 2024)

Parallel-in-Time Probabilistic Solutions for Time-Dependent Nonlinear Partial Differential Equations. - Sahel Iqbal; Hany Abdulsamad; Tripp Cator; Ulisses Braga-Neto; Simo Särkkä (MLSP, 2024)

Modelling pathwise uncertainty of Stochastic Differential Equations samplers via Probabilistic Numerics. - Yvann Le Fay; Simo Särkkä; Adrien Corenflos (CoRR, 2024)

Quantum-Assisted Hilbert-Space Gaussian Process Regression. - Ahmad Farooq; Cristian A. Galvis-Florez; Simo Särkkä (CoRR, 2024)

Physics-Informed Machine Learning for Grade Prediction in Froth Flotation. - Mahdi Nasiri; Sahel Iqbal; Simo Särkkä (CoRR, 2024)

Recursive Nested Filtering for Efficient Amortized Bayesian Experimental Design. - Sahel Iqbal; Hany Abdulsamad; Sara Pérez-Vieites; Simo Särkkä; Adrien Corenflos (CoRR, 2024)

A Parallel-in-Time Newton's Method for Nonlinear Model Predictive Control. - Casian Iacob; Hany Abdulsamad; Simo Särkkä (CoRR, 2024)

Parallel-in-Time Probabilistic Numerical ODE Solvers. - Nathanael Bosch; Adrien Corenflos; Fatemeh Yaghoobi; Filip Tronarp; Philipp Hennig; Simo Särkkä (J. Mach. Learn. Res., 2024)

Joint Use of a Low Thermal Resolution Thermal Camera and an RGB Camera for Respiration Measurement. - Zaeed Khan; Matias Rusanen; Miika Arvonen; Timo Leppänen; Simo Särkkä (IEEE Trans. Instrum. Meas., 2024)

Spacing Vector and Varying Distance Constrained Positioning Using Dual Feet-Mounted IMUs. - Xiaofeng Ma; Simo Särkkä (IEEE Trans. Instrum. Meas., 2024)

Baltic Sea Ice Dataset. - Ajinkya Gorad; Toni Hammarberg; Henrik Ramm-Schmidt; Simo Särkkä (Zenodo, 2024)

Gaussian-Based Parametric Bijections for Automatic Projection Filters. - Muhammad F. Emzir; Zheng Zhao 004; Lahouari Cheded; Simo Särkkä (IEEE Trans. Autom. Control., 2024)

Rao-Blackwellized Particle Filter Using Noise Adaptive Kalman Filter for Fully Mixing State-Space Models. - Tabish Badar; Simo Särkkä; Zheng Zhao 004; Arto Visala (IEEE Trans. Aerosp. Electron. Syst., 2024)

Conditioning diffusion models by explicit forward-backward bridging. - Adrien Corenflos; Zheng Zhao 004; Thomas B. Schön; Simo Särkkä; Jens Sjölund (AISTATS, 2025)

Quantum-Assisted Gaussian Process Regression Using Random Fourier Features. - Cristian A. Galvis-Florez; Ahmad Farooq; Simo Särkkä (QSW, 2025)

Parallel Square-Root Statistical Linear Regression for Inference in Nonlinear State Space Models. - Fatemeh Yaghoobi; Adrien Corenflos; Sakira Hassan; Simo Särkkä (SIAM J. Sci. Comput., 2025)

Parallel State Estimation for Systems With Integrated Measurements. - Fatemeh Yaghoobi; Simo Särkkä (IEEE Signal Process. Lett., 2025)

Provable Quantum Algorithm Advantage for Gaussian Process Quadrature. - Cristian A. Galvis-Florez; Ahmad Farooq; Simo Särkkä (Trans. Mach. Learn. Res., 2025)

Gaussian Multi-Target Filtering With Target Dynamics Driven by a Stochastic Differential Equation. - Ángel F. García-Fernández; Simo Särkkä (IEEE Trans. Signal Process., 2025)

Communication-Efficient Distributed Kalman Filtering using ADMM. - Muhammad Iqbal; Kundan Kumar; Simo Särkkä (CoRR, 2025)

Statistical Linear Regression Approach to Kalman Filtering and Smoothing under Cyber-Attacks. - Kundan Kumar; Muhammad Iqbal; Simo Särkkä (CoRR, 2025)

Sequential Monte Carlo for Policy Optimization in Continuous POMDPs. - Hany Abdulsamad; Sahel Iqbal; Simo Särkkä (CoRR, 2025)

Temporal Parallelization of the HJB Equation and Continuous-Time Linear Quadratic Control. - Simo Särkkä; Ángel F. García-Fernández (IEEE Trans. Autom. Control., 2025)

Determination of Particle-Size Distributions from Light-Scattering Measurement Using Constrained Gaussian Process Regression. - Fahime Seyedheydari; Mahdi Nasiri; Marcin Minkowski; Simo Särkkä (CoRR, 2025)