Simo Särkkä

Orcid: 0000-0002-7031-9354

Affiliations:
  • Aalto University, Finland


According to our database1, Simo Särkkä authored at least 201 papers between 2000 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Rao-Blackwellized Particle Filter Using Noise Adaptive Kalman Filter for Fully Mixing State-Space Models.
IEEE Trans. Aerosp. Electron. Syst., October, 2024

Gaussian-Based Parametric Bijections for Automatic Projection Filters.
IEEE Trans. Autom. Control., May, 2024

Spacing Vector and Varying Distance Constrained Positioning Using Dual Feet-Mounted IMUs.
IEEE Trans. Instrum. Meas., 2024

Joint Use of a Low Thermal Resolution Thermal Camera and an RGB Camera for Respiration Measurement.
IEEE Trans. Instrum. Meas., 2024

Parallel-in-Time Probabilistic Numerical ODE Solvers.
J. Mach. Learn. Res., 2024

Parallel state estimation for systems with integrated measurements.
CoRR, 2024

A Parallel-in-Time Newton's Method for Nonlinear Model Predictive Control.
CoRR, 2024

Recursive Nested Filtering for Efficient Amortized Bayesian Experimental Design.
CoRR, 2024

Physics-Informed Machine Learning for Grade Prediction in Froth Flotation.
CoRR, 2024

Conditioning diffusion models by explicit forward-backward bridging.
CoRR, 2024

Quantum-Assisted Hilbert-Space Gaussian Process Regression.
CoRR, 2024

Modelling pathwise uncertainty of Stochastic Differential Equations samplers via Probabilistic Numerics.
CoRR, 2024

Parallel-in-Time Probabilistic Solutions for Time-Dependent Nonlinear Partial Differential Equations.
Proceedings of the 34th IEEE International Workshop on Machine Learning for Signal Processing, 2024

Risk-Sensitive Filtering under False Data Injection Attacks.
Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2024

Nesting Particle Filters for Experimental Design in Dynamical Systems.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Gibbs Sampler for Bayesian Nonparametric State-Space Models.
Proceedings of the IEEE International Conference on Acoustics, 2024

Stacked iterated posterior linearization filter.
Proceedings of the 27th International Conference on Information Fusion, 2024

Polynomial Chaos Expansion Based Rauch-Tung-Striebel Smoothers.
Proceedings of the 27th International Conference on Information Fusion, 2024

2023
Fourier-Hermite Dynamic Programming for Optimal Control.
IEEE Trans. Autom. Control., October, 2023

Temporal Parallelization of Dynamic Programming and Linear Quadratic Control.
IEEE Trans. Autom. Control., February, 2023

Probabilistic Estimation of Instantaneous Frequencies of Chirp Signals.
IEEE Trans. Signal Process., 2023

A probabilistic Taylor expansion with Gaussian processes.
Trans. Mach. Learn. Res., 2023

Multidimensional projection filters via automatic differentiation and sparse-grid integration.
Signal Process., 2023

Online pole segmentation on range images for long-term LiDAR localization in urban environments.
Robotics Auton. Syst., 2023

Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees.
J. Mach. Learn. Res., 2023

Risk-Sensitive Stochastic Optimal Control as Rao-Blackwellized Markovian Score Climbing.
CoRR, 2023

Auxiliary MCMC and particle Gibbs samplers for parallelisable inference in latent dynamical systems.
CoRR, 2023

Deep Learning Based Projection Domain Metal Segmentation for Metal Artifact Reduction in Cone Beam Computed Tomography.
IEEE Access, 2023

Fast Dynamic Programming in Trees in the MPC Model.
Proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures, 2023

Vessel Bearing Estimation Using Visible and Thermal Imaging.
Proceedings of the Image Analysis - 22nd Scandinavian Conference, 2023

Single Qubit State Estimation on NISQ Devices with Limited Resources and SIC-POVMs.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Rao-Blackwellized Monte Carlo Data Association With Deep Metric For Object Tracking.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Nonparametric modeling of the composite effect of multiple nutrients on blood glucose dynamics.
Proceedings of the Machine Learning for Health, 2023

Indoor Positioning Methods Based on Dual Feet-Mounted IMUs With Distance Constraints.
Proceedings of the 13th International Conference on Indoor Positioning and Indoor Navigation, 2023

A Recursive Newton Method for Smoothing in Nonlinear State Space Models.
Proceedings of the 31st European Signal Processing Conference, 2023

On The Temporal Parallelisation of The Viterbi Algorithm.
Proceedings of the 31st European Signal Processing Conference, 2023

2022
Guest Editorial: MLSP 2020 Special Issue.
J. Signal Process. Syst., 2022

Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review.
IEEE Trans. Intell. Transp. Syst., 2022

Autonomous Tracking and State Estimation With Generalized Group Lasso.
IEEE Trans. Cybern., 2022

Non-Linear Gaussian Smoothing With Taylor Moment Expansion.
IEEE Signal Process. Lett., 2022

De-Sequentialized Monte Carlo: a parallel-in-time particle smoother.
J. Mach. Learn. Res., 2022

Temporal Parallelisation of the HJB Equation and Continuous-Time Linear Quadratic Control.
CoRR, 2022

Metal artifact correction in cone beam computed tomography using synthetic X-ray data.
CoRR, 2022

Parallel square-root statistical linear regression for inference in nonlinear state space models.
CoRR, 2022

Uncertainty-Aware Deep Learning Methods for Robust Diabetic Retinopathy Classification.
IEEE Access, 2022

Continuous-Discrete Filtering and Smoothing on Submanifolds of Euclidean Space.
Proceedings of the 25th International Conference on Information Fusion, 2022

Posterior linearisation filter for non-linear state transformation noises.
Proceedings of the 25th International Conference on Information Fusion, 2022

Fast optimize-and-sample method for differentiable Galerkin approximations of multi-layered Gaussian process priors.
Proceedings of the 25th International Conference on Information Fusion, 2022

Temporal Gaussian Process Regression in Logarithmic Time.
Proceedings of the 25th International Conference on Information Fusion, 2022

2021
Temporal Parallelization of Inference in Hidden Markov Models.
IEEE Trans. Signal Process., 2021

Taylor Moment Expansion for Continuous-Discrete Gaussian Filtering.
IEEE Trans. Autom. Control., 2021

Temporal Parallelization of Bayesian Smoothers.
IEEE Trans. Autom. Control., 2021

Improved Calibration of Numerical Integration Error in Sigma-Point Filters.
IEEE Trans. Autom. Control., 2021

Deep state-space Gaussian processes.
Stat. Comput., 2021

Bayesian ODE solvers: the maximum a posteriori estimate.
Stat. Comput., 2021

Correction to: Kernel-based interpolation at approximate Fekete points.
Numer. Algorithms, 2021

Kernel-based interpolation at approximate Fekete points.
Numer. Algorithms, 2021

Temporal Parallelisation of Dynamic Programming and Linear Quadratic Control.
CoRR, 2021

Gaussian Process Regression in Logarithmic Time.
CoRR, 2021

A Probabilistic Taylor Expansion with Applications in Filtering and Differential Equations.
CoRR, 2021

Gaussian Approximations of SDES in Metropolis-Adjusted Langevin Algorithms.
Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Metal Artifact Reduction In Cone-Beam Extremity Images Using Gated Convolutions.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Kalman filtering with empirical noise models.
Proceedings of the 11th International Conference on Localization and GNSS, 2021

Parallel Iterated Extended and Sigma-Point Kalman Smoothers.
Proceedings of the IEEE International Conference on Acoustics, 2021

Real-Time Tracking of Multiple Acoustical Sources Utilising Rao-Blackwellised Particle Filtering.
Proceedings of the 29th European Signal Processing Conference, 2021

2020
Kalman-based Spectro-Temporal ECG Analysis using Deep Convolutional Networks for Atrial Fibrillation Detection.
J. Signal Process. Syst., 2020

RSS Models for Respiration Rate Monitoring.
IEEE Trans. Mob. Comput., 2020

Importance Densities for Particle Filtering Using Iterated Conditional Expectations.
IEEE Signal Process. Lett., 2020

Variable Splitting Methods for Constrained State Estimation in Partially Observed Markov Processes.
IEEE Signal Process. Lett., 2020

Gaussian mixture models for signal mapping and positioning.
Signal Process., 2020

On Stability of a Class of Filters for Nonlinear Stochastic Systems.
SIAM J. Control. Optim., 2020

Hilbert space methods for reduced-rank Gaussian process regression.
Stat. Comput., 2020

Maximum Likelihood Estimation and Uncertainty Quantification for Gaussian Process Approximation of Deterministic Functions.
SIAM/ASA J. Uncertain. Quantification, 2020

A survey of Monte Carlo methods for parameter estimation.
EURASIP J. Adv. Signal Process., 2020

Enhancing Industrial X-ray Tomography by Data-Centric Statistical Methods.
CoRR, 2020

Worst-case optimal approximation with increasingly flat Gaussian kernels.
Adv. Comput. Math., 2020

Machine Learning Methods for Neonatal Mortality and Morbidity Classification.
IEEE Access, 2020

Parameter Estimation in Non-Linear State-Space Models by Automatic Differentiation of Non-Linear Kalman Filters.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

State-Space Gaussian Process for Drift Estimation in Stochastic Differential Equations.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Levenberg-Marquardt and Line-Search Extended Kalman Smoothers.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Augmented Sigma-Point Lagrangian Splitting Method for Sparse Nonlinear State Estimation.
Proceedings of the 28th European Signal Processing Conference, 2020

Respiratory Pattern Recognition from Low-Resolution Thermal Imaging.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

LSD_2 - Joint Denoising and Deblurring of Short and Long Exposure Images with CNNs.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019
Rao-Blackwellized Posterior Linearization Backward SLAM.
IEEE Trans. Veh. Technol., 2019

Gaussian Target Tracking With Direction-of-Arrival von Mises-Fisher Measurements.
IEEE Trans. Signal Process., 2019

Iterated Extended Kalman Smoother-Based Variable Splitting for L<sub>1</sub>-Regularized State Estimation.
IEEE Trans. Signal Process., 2019

Gaussian Process Latent Force Models for Learning and Stochastic Control of Physical Systems.
IEEE Trans. Autom. Control., 2019

Rao-Blackwellized Gaussian Smoothing.
IEEE Trans. Autom. Control., 2019

Student's $t$-Filters for Noise Scale Estimation.
IEEE Signal Process. Lett., 2019

Gaussian Process Classification Using Posterior Linearization.
IEEE Signal Process. Lett., 2019

Iterative statistical linear regression for Gaussian smoothing in continuous-time non-linear stochastic dynamic systems.
Signal Process., 2019

Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective.
Stat. Comput., 2019

A probabilistic model for the numerical solution of initial value problems.
Stat. Comput., 2019

Symmetry exploits for Bayesian cubature methods.
Stat. Comput., 2019

On the positivity and magnitudes of Bayesian quadrature weights.
Stat. Comput., 2019

Numerical integration as a finite matrix approximation to multiplication operator.
J. Comput. Appl. Math., 2019

On the Convergence of Numerical Integration as a Finite Matrix Approximation to Multiplication Operator.
CoRR, 2019

Automated Polysomnography Analysis for Detection of Non-Apneic and Non-Hypopneic Arousals using Feature Engineering and a Bidirectional LSTM Network.
CoRR, 2019

The Use of Gaussian Processes in System Identification.
CoRR, 2019

Temporal Parallelization of Bayesian Filters and Smoothers.
CoRR, 2019

1D Convolutional Neural Network Models for Sleep Arousal Detection.
CoRR, 2019

Gyroscope-Aided Motion Deblurring with Deep Networks.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Asymptotics of Maximum Likelihood Parameter Estimates For Gaussian Processes: The Ornstein-Uhlenbeck Prior.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Rejection-Sampling-Based Ancestor Sampling for Particle Gibbs.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Regularized State Estimation And Parameter Learning Via Augmented Lagrangian Kalman Smoother Method.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Hilbert-Space Reduced-Rank Methods For Deep Gaussian Processes.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Updates in Bayesian Filtering by Continuous Projections on a Manifold of Densities.
Proceedings of the IEEE International Conference on Acoustics, 2019

Partitioned Update Binomial Gaussian Mixture Filter.
Proceedings of the 22th International Conference on Information Fusion, 2019

Joint Calibration of Inertial Sensors and Magnetometers using von Mises-Fisher Filtering and Expectation Maximization.
Proceedings of the 22th International Conference on Information Fusion, 2019

2018
Cooperative Localization Using Posterior Linearization Belief Propagation.
IEEE Trans. Veh. Technol., 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. Sci. Comput., 2018

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

LSD<sub>2</sub> - Joint Denoising and Deblurring of Short and Long Exposure Images with Convolutional Neural Networks.
CoRR, 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

A Bayes-Sard Cubature Method.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 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

Fast Motion Deblurring for Feature Detection and Matching Using Inertial Measurements.
Proceedings of the 24th International Conference on Pattern Recognition, 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 S<sup>2</sup> 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

Combined Analysis-L1 and Total Variation ADMM with Applications to MEG Brain Imaging and Signal Reconstruction.
Proceedings of the 26th European Signal Processing Conference, 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

Automatic Sleep Arousal Detection Using Multimodal Biosignal Analysis.
Proceedings of the Computing in Cardiology, 2018

Bounds on the Covariance Matrix of a Class of Kalman-Bucy Filters for Systems with Non-Linear Dynamics.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017
Iterated Posterior Linearization Smoother.
IEEE Trans. Autom. Control., 2017

Statistical analysis of differential equations: introducing probability measures on numerical solutions.
Stat. Comput., 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 Process., 2016

Rao-Blackwellized Particle Smoothers for Conditionally Linear Gaussian Models.
IEEE J. Sel. Top. Signal Process., 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 Process., 2015

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

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

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

A Bayesian particle filtering method for brain source localisation.
Digit. Signal Process., 2015

Adaptive Metropolis algorithm using variational Bayesian adaptive Kalman filter.
Comput. Stat. Data Anal., 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 Process., 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 L<sup>4</sup> 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 L<sup>4</sup> 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 Process., 2013

Parameter estimation in stochastic differential equations with Markov chain Monte Carlo and non-linear Kalman filtering.
Comput. Stat., 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. Autom. Control., 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

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
Accurate Discretization of Analog Audio Filters With Application to Parametric Equalizer Design.
IEEE ACM Trans. Audio Speech Lang. Process., 2011

Correction to "On Gaussian Optimal Smoothing of Nonlinear State Space Models" [Aug 10 1938-1941].
IEEE Trans. Autom. Control., 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. Autom. Control., 2010

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

2009
Recursive Noise Adaptive Kalman Filtering by Variational Bayesian Approximations.
IEEE Trans. Autom. Control., 2009

2008
Unscented Rauch-Tung-Striebel Smoother.
IEEE Trans. Autom. Control., 2008

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

Rao-Blackwellized particle filter for multiple target tracking.
Inf. 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.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000


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