Research Output per year
Research Output
2020
Gaussian mixture models for signal mapping and positioning
Raitoharju, M., García-Fernández, Á. F., Hostettler, R., Piché, R. & Särkkä, S., 1 Mar 2020, In : Signal Processing. 168, 11 p., 107330.Research output: Contribution to journal › Article › Scientific › peer-review
Importance Densities for Particle Filtering Using Iterated Conditional Expectations
Hostettler, R., Tronarp, F., Garcia-Fernandez, A. F. & Sarkka, S., 1 Jan 2020, In : IEEE Signal Processing Letters. 27, p. 211-215 5 p., 8951063.Research output: Contribution to journal › Article › Scientific › peer-review
Kalman-based Spectro-Temporal ECG Analysis using Deep Convolutional Networks for Atrial Fibrillation Detection
Zhao, Z., Särkkä, S. & Rad, A. B., 30 Apr 2020, In : Journal of Signal Processing Systems. 16 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Kernel-based interpolation at approximate Fekete points
Karvonen, T., Särkkä, S. & Tanaka, K., 10 Jul 2020, In : NUMERICAL ALGORITHMS. 24 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Machine Learning Methods for Neonatal Mortality and Morbidity Classification
Jaskari, J., Myllarinen, J., Leskinen, M., Rad, A. B., Hollmén, J., Andersson, S. & Sarkka, S., 2 Jul 2020, In : IEEE Access. 8, p. 123347-123358 12 p., 9131772.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Multispectral photon-counting for medical imaging and beam characterization
Brücken, E., Bharthuar, S., Emzir, M., Golovleva, M., Gädda, A., Hostettler, R., Härkönen, J., Kirschenmann, S., Litichevskyi, V., Luukka, P., Martikainen, L., Naaranoja, T., Nincǎ, I., Ott, J., Petrow, H., Purisha, Z., Siiskonen, T., Särkkä, S., Tikkanen, J., Tuuva, T. & 1 others, , 18 Feb 2020, In : Journal of Instrumentation. 15, 2, 11 p., C02024.Research output: Contribution to journal › Article › Scientific › peer-review
RSS Models for Respiration Rate Monitoring
Yiǧitler, H., Kaltiokallio, O., Hostettler, R., Abrar, A. S., Jäntti, R., Patwari, N. & Särkkä, S., 1 Mar 2020, In : IEEE Transactions on Mobile Computing. 19, 3, p. 680-696 17 p., 8634923.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Variable Splitting Methods for Constrained State Estimation in Partially Observed Markov Processes
Gao, R., Tronarp, F. & Särkkä, S., 2020, In : IEEE Signal Processing Letters. 27, p. 1305-1309 5 p., 9143395.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Worst-case optimal approximation with increasingly flat Gaussian kernels
Karvonen, T. & Särkkä, S., 1 Apr 2020, In : ADVANCES IN COMPUTATIONAL MATHEMATICS. 46, 2, 17 p., 21.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
2019
A probabilistic model for the numerical solution of initial value problems
Schober, M., Särkkä, S. & Hennig, P., 15 Jan 2019, In : STATISTICS AND COMPUTING. 29, 1, p. 99-122 24 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Gaussian kernel quadrature at scaled Gauss–Hermite nodes
Karvonen, T. & Särkkä, S., 2019, In : BIT - Numerical Mathematics. p. 877–902 26 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Gaussian process classification using posterior linearization
Garcia-Fernandez, A. F., Tronarp, F. & Särkkä, S., 1 May 2019, In : IEEE Signal Processing Letters. 26, 5, p. 735-739 5 p., 8673324.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Gaussian Process Latent Force Models for Learning and Stochastic Control of Physical Systems
särkkä, S., Alvarez, M. A. & Lawrence, N. D., 2019, In : IEEE Transactions on Automatic Control. 64, 7, p. 2953-2960 8 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Gaussian Target Tracking With Direction-of-Arrival von Mises–Fisher Measurements
García-Fernández, Á. F., Tronarp, F. & Särkkä, S., 1 Jun 2019, In : IEEE Transactions on Signal Processing. 67, 11, p. 2960-2972 13 p., 8691412.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Hilbert space methods for reduced-rank Gaussian process regression
Solin, A. & Särkkä, S., 2019, In : STATISTICS AND COMPUTING. 28 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Iterated Extended Kalman Smoother-Based Variable Splitting for L-1-Regularized State Estimation
Gao, R., Tronarp, F. & Särkkä, S., 1 Oct 2019, In : IEEE Transactions on Signal Processing. 67, 19, p. 5078-5092 15 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Iterative statistical linear regression for Gaussian smoothing in continuous-time non-linear stochastic dynamic systems
Tronarp, F. & Särkkä, S., 1 Jun 2019, In : Signal Processing. 159, p. 1-12 12 p.Research output: Contribution to journal › Article › Scientific › peer-review
Numerical integration as a finite matrix approximation to multiplication operator
Sarmavuori, J. & Särkkä, S., 1 Jun 2019, In : Journal of Computational and Applied Mathematics. 353, p. 283-291 9 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
On the positivity and magnitudes of Bayesian quadrature weights
Karvonen, T., Kanagawa, M. & Särkkä, S., 4 Oct 2019, In : STATISTICS AND COMPUTING. 17 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Probabilistic approach to limited-data computed tomography reconstruction
Purisha, Z., Jidling, C., Wahlstrom, N., Schön, T. B. & Särkkä, S., Oct 2019, In : Inverse Problems. 35, 10, 20 p., 105004.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: A new perspective
Tronarp, F., Kersting, H., Särkkä, S. & Hennig, P., 18 Sep 2019, In : STATISTICS AND COMPUTING. 29, p. 1297-1315 19 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Rao-Blackwellized Gaussian Smoothing
Hostettler, R. & Särkkä, S., 1 Jan 2019, In : IEEE Transactions on Automatic Control. 64, 1, p. 305-312 8 p., 8340820.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Rao-Blackwellized Posterior Linearization Backward SLAM
García-Fernández, Á. F., Hostettler, R. & Särkkä, S., 1 May 2019, In : IEEE Transactions on Vehicular Technology. 68, 5, p. 4734-4747 14 p., 8662708.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Student's t-Filters for Noise Scale Estimation
Tronarp, F., Karvonen, T. & Särkkä, S., 1 Feb 2019, In : IEEE Signal Processing Letters. 26, 2, p. 352-356 5 p., 8606947.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Symmetry exploits for Bayesian cubature methods
Karvonen, T., Särkkä, S. & Oates, C. J., 1 Jan 2019, In : STATISTICS AND COMPUTING. 29, 6, p. 1231–1248 18 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
2018
Cooperative localization using posterior linearization belief propagation
Garcia-Fernandez, A. F., Svensson, L. & Särkkä, S., 2018, In : IEEE Transactions on Vehicular Technology. 67, 1, p. 832-836Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Fully symmetric kernel quadrature
Karvonen, T. & Särkkä, S., 2018, In : SIAM Journal on Scientific Computing. 40, 2, p. A697-A720 24 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Gaussian process classification for prediction of in-hospital mortality among preterm infants
Rinta-Koski, O. P., Särkkä, S., Hollmén, J., Leskinen, M. & Andersson, S., 2018, In : Neurocomputing. 298, p. 134-141Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Iterative Filtering and Smoothing In Non-Linear and Non-Gaussian Systems Using Conditional Moments
Tronarp, F., Garcia Fernandez, A. & Särkkä, S., 17 Jan 2018, In : IEEE Signal Processing Letters. 25, 3, p. 408-412 5 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Modeling and Interpolation of the Ambient Magnetic Field by Gaussian Processes
Solin, A., Kok, M., Wahlstrom, N., Schon, T. B. & Sarkka, S., 2018, In : IEEE Transactions on Robotics. 34, 4, p. 1112-1127Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
Sparse Approximations of Fractional Matérn Fields
Roininen, L., Lasanen, S., Orispää, M. & Särkkä, S., 2018, In : Scandinavian Journal of Statistics. 45, 1, p. 194–216 23 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Variational Bayesian adaptation of noise covariances in multiple target tracking problems
Hosseini, S. S., Jamali, M. M. & Särkkä, S., 1 Jul 2018, In : Measurement: Journal of the International Measurement Confederation. 122, p. 14-19 6 p.Research output: Contribution to journal › Article › Scientific › peer-review
2017
Iterated posterior linearisation smoother
Garcia Fernandez, A., Svensson, L. & Särkkä, S., 2017, In : IEEE Transactions on Automatic Control. 62, 4, p. 2056-2063 8 p., 7515187.Research output: Contribution to journal › Article › Scientific › peer-review
Statistical analysis of differential equations: introducing probability measures on numerical solutions
Conrad, P. R., Girolami, M., Särkkä, S., Stuart, A. & Zygalakis, K., 1 Jul 2017, In : STATISTICS AND COMPUTING. 27, 4, p. 1065-1082 18 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
2016
Moment conditions for convergence of particle filters with unbounded importance weights
Mbalawata, I. S. & Särkkä, S., Jan 2016, In : Signal Processing. 118, p. 133-138 6 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
On the relation between Gaussian process quadratures and sigma-point methods
Särkkä, S., Hartikainen, J., Svensson, L. & Sandblom, F., Jun 2016, In : JOURNAL OF ADVANCES IN INFORMATION FUSION. 11, 1, p. 31-46Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Rao-Blackwellized Particle Smoothers for Conditionally Linear Gaussian Models
Lindsten, F., Bunch, P., Särkkä, S., Schön, T. B. & Godsill, S. J., Mar 2016, In : IEEE Journal of Selected Topics in Signal Processing. 10, 2, p. 353-365 13 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Sigma-Point Filtering and Smoothing Based Parameter Estimation in Nonlinear Dynamic Systems
Kokkala, J., Solin, A. & Särkkä, S., 2016, In : JOURNAL OF ADVANCES IN INFORMATION FUSION. 11, 1, p. 15-30Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
2015
A Bayesian Particle Filtering Method For Brain Source Localisation
Chen, X., Särkkä, S. & Godsill, S., 2015, In : Digital Signal Processing. 47, p. 192-204Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Adaptive Metropolis algorithm using variational Bayesian adaptive Kalman filter
Mbalawata, I. S., Särkkä, S., Vihola, M. & Haario, H., 2015, In : Computational Statistics and Data Analysis. 83, p. 101-115Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Batch nonlinear continuous-time trajectory estimation as exactly sparse Gaussian process regression
Anderson, S., Barfoot, T. D., Tong, C. H. & Särkkä, S., 2015, In : Autonomous Robots. 39, 3, p. 221-238Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Combining particle MCMC with Rao-Blackwellized Monte Carlo data association for parameter estimation in multiple target tracking
Kokkala, J. & Särkkä, S., 2015, In : Digital Signal Processing. 47, p. 84-95Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Gaussian filtering and variational approximations for Bayesian smoothing in continuous-discrete stochastic dynamic systems
Ala-Luhtala, J., Särkkä, S. & Piche, R., 2015, In : Signal Processing. 111, 1, p. 124-136Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
On the (non-)convergence of particle filters with Gaussian importance distributions
Kokkala, J. & Särkkä, S., 2015, In : IFAC-PapersOnLine. 48, 28, p. 793-798 6 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Posterior inference on parameters of stochastic differential equations via non-linear Gaussian filtering and adaptive MCMC
Särkkä, S., Hartikainen, J., Mbalawata, I. S. & Haario, H., 2015, In : STATISTICS AND COMPUTING. 25, 2, p. 427-437Research output: Contribution to journal › Article › Scientific › peer-review
Posterior Linearization Filter: Principles and Implementation Using Sigma Points
Garcia-Fernandez, A. F., Svensson, L., Morelande, M. R. & Särkkä, S., 2015, In : IEEE Transactions on Signal Processing. 63, 20, p. 5561-5573Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
File
2014
Series Expansion Approximations of Brownian Motion for Non-Linear Kalman Filtering of Diffusion Processes
Lyons, S. M. J., Särkkä, S. & Storkey, A. J., 2014, In : IEEE Transactions on Signal Processing. 6, p. 1514-1524Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
2013
Gaussian filtering and smoothing for continuous-discrete dynamic systems
Särkkä, S. & Sarmavuori, J., 2013, In : Signal Processing. 93, 2, p. 500-510Research output: Contribution to journal › Article › Scientific › peer-review
Infinite-dimensional Bayesian filtering for detection of quasiperiodic phenomena in spatiotemporal data
Solin, A. & Särkkä, S., 2013, In : Physical Review E. 88, 5Research output: Contribution to journal › Article › Scientific › peer-review
Open Access
Parameter estimation in stochastic differential equations with Markov chain Monte Carlo and non-linear Kalman filtering
Mbalawata, I. S., Särkkä, S. & Haario, H., 2013, In : Computational Statistics. 28, 3, p. 1195-1223Research output: Contribution to journal › Article › Scientific › peer-review