Thomas B. Schön

Johan Dahlin, Thomas B. Schön, Andreas Svensson, 2015, 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

Identification of Hammerstein-Wiener models

Lennart Ljung, Thomas B. Schön, Brett Ninness, 2013, Autom..

Preliminary Notes on the Interplay Between Estimation and Optimization Problems

Thomas B. Schön, Thomas Bo Schön, 2009 .

Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding pdf

Thomas B. Schön, Dave Zachariah, Muhammad Osama, 2019, ICML.

A General Convergence Result for Particle Filtering

Xiao-Li Hu, Lennart Ljung, Thomas B. Schön, 2011, IEEE Transactions on Signal Processing.

Deep Energy-Based NARX Models pdf

Thomas B. Schön, Adrian Wills, Fredrik K. Gustafsson, 2020, IFAC-PapersOnLine.

Learning Deep Conditional Target Densities for Accurate Regression

Thomas B. Schön, Martin Danelljan, Goutam Bhat, 2019 .

A Basic Convergence Result for Particle Filtering

Xiao-Li Hu, Lennart Ljung, Thomas B. Schön, 2008, IEEE Transactions on Signal Processing.

Capacity estimation of two-dimensional channels using Sequential Monte Carlo

Fredrik Lindsten, Thomas B. Schön, C. A. Naesseth, 2014, 2014 IEEE Information Theory Workshop (ITW 2014).

Deep kernel learning for integral measurements pdf

Thomas B. Schön, Adrian Wills, Carl Jidling, 2019, ArXiv.

On computational methods for nonlinear estimation

Thomas B. Schön, Thomas Bo Schön, 2003 .

Backward Simulation Methods for Monte Carlo Statistical Inference

Fredrik Lindsten, Thomas B. Schön, Thomas Bo Schön, 2013, Found. Trends Mach. Learn..

Online Sparse Gaussian Process Training with Input Noise pdf

Michel Verhaegen, Thomas B. Schön, Jan-Willem van Wingerden, 2016, ArXiv.

Particle Filter in Practice

Thomas B. Schön, Fredrik Gustafsson, Rickard Karlsson, 2011 .

A Nonlinear Least-Squares Approach to the SLAM Problem

Thomas B. Schön, Fredrik Gustafsson, Zoran Sjanic, 2011 .

Automated learning with a probabilistic programming language: Birch pdf

Thomas B. Schön, Lawrence M. Murray, Thomas Bo Schön, 2018, Annu. Rev. Control..

On the Smoothness of Nonlinear System Identification pdf

Thomas B. Schön, Koen Tiels, Luis A. Aguirre, 2019, Autom..

A new algorithm for calibrating a combined camera and IMU sensor unit

Thomas B. Schön, Fredrik Gustafsson, Jeroen D. Hol, 2008, 2008 10th International Conference on Control, Automation, Robotics and Vision.

Data-Driven Impulse Response Regularization via Deep Learning pdf

Thomas B. Schön, Niklas Wahlstrom, Carl R. Andersson, 2018, ArXiv.

Linearly Constrained Neural Networks pdf

Thomas B. Schön, Adrian Wills, Carl Jidling, 2020, ArXiv.

On the construction of probabilistic Newton-type algorithms

Thomas B. Schön, Adrian Wills, 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

Deep Convolutional Networks in System Identification

Thomas B. Schön, Koen Tiels, Niklas Wahlstrom, 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

Detecting and positioning overtaking vehicles using 1D optical flow

Jacob Roll, Johan Dahlin, Thomas B. Schön, 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

High-Dimensional Filtering Using Nested Sequential Monte Carlo

Fredrik Lindsten, Thomas B. Schön, C. A. Naesseth, 2016, IEEE Transactions on Signal Processing.

A framework for simultaneous localization and mapping utilizing model structure

Thomas B. Schön, Fredrik Gustafsson, Rickard Karlsson, 2007, 2007 10th International Conference on Information Fusion.

Relative pose calibration of a spherical camera and an IMU

Thomas B. Schön, Fredrik Gustafsson, Jeroen D. Hol, 2008, 2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality.

Indoor Photorealistic 3D Mapping using Stereo Images from SLR Cameras

Thomas B. Schön, Thomas Beckman, Viktor Kolbe, 2009 .

Learning to close loops from range data

Thomas B. Schön, Karl Granström, Fabio Tozeto Ramos, 2011, Int. J. Robotics Res..

THE MARGINALIZED PARTICLE FILTER - ANALYSIS, APPLICATIONS AND GENERALIZATIONS

Thomas B. Schön, Fredrik Gustafsson, Rickard Karlsson, 2007 .

A flexible state space model for learning nonlinear dynamical systems pdf

Thomas B. Schön, Andreas Svensson, Thomas Bo Schön, 2016, Autom..

Maximum likelihood identification of stable linear dynamical systems

Thomas B. Schön, Ian R. Manchester, Jack Umenberger, 2018, Autom..

Nonlinear state space smoothing using the conditional particle filter pdf

Thomas B. Schön, Andreas Svensson, Manon Kok, 2015, ArXiv.

Decentralization of particle filters using arbitrary state decomposition

Henrik Ohlsson, Lennart Ljung, Tianshi Chen, 2010, 49th IEEE Conference on Decision and Control (CDC).

Robust exploration in linear quadratic reinforcement learning

Thomas B. Schön, Håkan Hjalmarsson, Mina Ferizbegovic, 2019, NeurIPS.

Deep Learning and System Identification

Thomas B. Schön, Koen Tiels, Lennart Ljung, 2020, IFAC-PapersOnLine.

Torchlight Navigation

Michael Felsberg, Anders Ynnerman, Thomas B. Schön, 2010, 2010 20th International Conference on Pattern Recognition.

Regularized parametric system identification: a decision-theoretic formulation

Thomas B. Schön, Dave Zachariah, Johan Wågberg, 2017, 2018 Annual American Control Conference (ACC).

Mean and variance of the LQG cost function

Michel Verhaegen, Thomas B. Schön, Jan-Willem van Wingerden, 2016, Autom..

Fast particle filters for multi-rate sensors

Thomas B. Schön, Fredrik Gustafsson, David Törnqvist, 2007, 2007 15th European Signal Processing Conference.

Linear System Identification via EM with Latent Disturbances and Lagrangian Relaxation pdf

Thomas B. Schön, Ian R. Manchester, Jack Umenberger, 2016, ArXiv.

Learning convex bounds for linear quadratic control policy synthesis

Thomas B. Schön, Jack Umenberger, Thomas Bo Schön, 2018, NeurIPS.

Beyond exploding and vanishing gradients: analysing RNN training using attractors and smoothness

Thomas B. Schön, Koen Tiels, Luis A. Aguirre, 2019, AISTATS.

Robust auxiliary particle filters using multiple importance sampling

Thomas B. Schön, Joel Kronander, Thomas Bo Schön, 2014, 2014 IEEE Workshop on Statistical Signal Processing (SSP).

Identification of mixed linear/nonlinear state-space models

Fredrik Lindsten, Thomas B. Schön, Thomas Bo Schön, 2010, 49th IEEE Conference on Decision and Control (CDC).

Ancestor Sampling for Particle Gibbs

Fredrik Lindsten, Thomas B. Schön, Michael I. Jordan, 2012, NIPS.

The Elliptical Processes: a New Family of Flexible Stochastic Processes pdf

Thomas B. Schön, Jalil Taghia, Jens Sjölund, 2020, ArXiv.

A fast quasi-Newton-type method for large-scale stochastic optimisation pdf

Thomas B. Schön, Adrian Wills, Carl Jidling, 2018, IFAC-PapersOnLine.

Calibration of a magnetometer in combination with inertial sensors

Thomas B. Schön, Fredrik Gustafsson, Manon Kok, 2012, 2012 15th International Conference on Information Fusion.

Homework { Computational learning in dynamical systems

Thomas B. Schön, Thomas Bo Schön, 2014 .

On mixture reduction for multiple target tracking

Thomas B. Schön, Christian Lundquist, Umut Orguner, 2012, 2012 15th International Conference on Information Fusion.

Torch Guided Navigation

Anders Ynnerman, Thomas B. Schön, Fredrik Larsson, 2010 .

System identification of nonlinear state-space models

Thomas B. Schön, Brett Ninness, Adrian Wills, 2011, Autom..

Estimation of the Free Space in Front of a Moving Vehicle

Thomas B. Schön, Christian Lundquist, Thomas Bo Schön, 2009 .

Beyond Occam's Razor in System Identification: Double-Descent when Modeling Dynamics pdf

Thomas B. Schön, Adrian Wills, Antônio H. Ribeiro, 2020, ArXiv.

Elements of Sequential Monte Carlo

Fredrik Lindsten, Thomas B. Schön, C. A. Naesseth, 2019, Found. Trends Mach. Learn..

On the use of backward simulation in the particle Gibbs sampler

Fredrik Lindsten, Thomas B. Schön, Thomas Bo Schön, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Probabilistic Programming for Birth-Death Models of Evolution Using an Alive Particle Filter with Delayed Sampling

Thomas B. Schön, Lawrence M. Murray, Jan Kudlicka, 2019, UAI.

Learning Localized Spatio-Temporal Models From Streaming Data

Thomas B. Schön, Dave Zachariah, Muhammad Osama, 2018, ICML.

From Pixels to Torques: Policy Learning with Deep Dynamical Models pdf

Thomas B. Schön, Marc Peter Deisenroth, Niklas Wahlstrom, 2015, ICML 2015.

Constructing the Matrix Multilayer Perceptron and its Application to the VAE pdf

Fredrik Lindsten, Thomas B. Schön, Jalil Taghia, 2019, ArXiv.

Bayesian semiparametric Wiener system identification

Fredrik Lindsten, Thomas B. Schön, Michael I. Jordan, 2013, Autom..

Maximum likelihood calibration of a magnetometer using inertial sensors

Thomas B. Schön, Manon Kok, Thomas Bo Schön, 2014 .

Bayesian identification of state-space models via adaptive thermostats

Fredrik Lindsten, Thomas B. Schön, Jack Umenberger, 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

How to Train Your Energy-Based Model for Regression pdf

Radu Timofte, Thomas B. Schön, Martin Danelljan, 2020, BMVC.

MEMS-based inertial navigation based on a magnetic field map

Thomas B. Schön, Fredrik Gustafsson, Niklas Wahlstrom, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Comparing two recent particle filter implementations of Bayesian system identification

Thomas B. Schön, Andreas Svensson, 2016 .

Using Inertial Sensors for Position and Orientation Estimation pdf

Thomas B. Schön, Manon Kok, Jeroen D. Hol, 2017, Found. Trends Signal Process..

A New Structure Exploiting Derivation of Recursive Direct Weight Optimization

Thomas B. Schön, Liang Dai, 2015, IEEE Transactions on Automatic Control.

A Non-Degenerate Rao-Blackwellised Particle Filter for Estimating Static Parameters in Dynamical Models

Fredrik Lindsten, Thomas B. Schön, Lennart Svensson, 2012 .

Modeling and Interpolation of the Ambient Magnetic Field by Gaussian Processes

Thomas B. Schön, Simo Särkkä, Arno Solin, 2015, IEEE Transactions on Robotics.

Learning deep dynamical models from image pixels pdf

Thomas B. Schön, Marc Peter Deisenroth, Niklas Wahlstrom, 2014, ArXiv.

A Fast and Robust Algorithm for Orientation Estimation Using Inertial Sensors

Thomas B. Schön, Manon Kok, Thomas Bo Schön, 2019, IEEE Signal Processing Letters.

Estimating state-space models in innovations form using the expectation maximisation algorithm

Thomas B. Schön, Brett Ninness, Adrian Wills, 2010, 49th IEEE Conference on Decision and Control (CDC).

Deep State Space Models for Nonlinear System Identification pdf

Lennart Ljung, Thomas B. Schön, Niklas Wahlstrom, 2020, ArXiv.

Situational Awareness and Road Prediction for Trajectory Control Applications

Thomas B. Schön, Fredrik Gustafsson, Christian Lundquist, 2012 .

Rao-Blackwellized particle smoothers for mixed linear/nonlinear state-space models

Simon J. Godsill, Fredrik Lindsten, Thomas B. Schön, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

A note on state estimation as a convex optimization problem

Thomas B. Schön, Fredrik Gustafsson, Anders Hansson, 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

Marginalized particle filters for mixed linear/nonlinear state-space models

Thomas B. Schön, Fredrik Gustafsson, Per-Johan Nordlund, 2005, IEEE Transactions on Signal Processing.

Learning nonlinear state-space models using smooth particle-filter-based likelihood approximations pdf

Fredrik Lindsten, Thomas B. Schön, Andreas Svensson, 2017, ArXiv.

Particle Metropolis–Hastings using gradient and Hessian information

Johan Dahlin, Fredrik Lindsten, Thomas B. Schön, 2013, Statistics and Computing.

Bicycle tracking using ellipse extraction

Michael Felsberg, Thomas B. Schön, Fredrik Gustafsson, 2011, 14th International Conference on Information Fusion.

Experimental comparison of observers for tool position estimation of industrial robots

Thomas B. Schön, Mikael Norrlöf, Stig Moberg, 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

Marginalized Particle Filters for Nonlinear State-space Models

Thomas B. Schön, Fredrik Gustafsson, Per-Johan Nordlund, 2003 .

Particle gibbs with ancestor sampling

Fredrik Lindsten, Thomas B. Schön, Michael I. Jordan, 2014, J. Mach. Learn. Res..

Nonlinear Input Design as Optimal Control of a Hamiltonian System

Thomas B. Schön, Jack Umenberger, Thomas Bo Schön, 2019, IEEE Control Systems Letters.

Probabilistic programming allows for automated inference in factor graph models

Thomas B. Schön, Matteo Scandella, Lawrence M. Murray, 2018 .

Real-time video based lighting using GPU raytracing

Johan Dahlin, Thomas B. Schön, Daniel Jönsson, 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).

How consistent is my model with the data? Information-Theoretic Model Check pdf

Thomas B. Schön, Dave Zachariah, Andreas Svensson, 2017, ArXiv.

Decentralized Particle Filter With Arbitrary State Decomposition

Henrik Ohlsson, Lennart Ljung, Thomas B. Schön, 2011, IEEE Transactions on Signal Processing.

Backward sequential Monte Carlo for marginal smoothing

Johan Dahlin, Thomas B. Schön, Joel Kronander, 2014, 2014 IEEE Workshop on Statistical Signal Processing (SSP).

Estimation of general nonlinear state-space systems

Thomas B. Schön, Brett Ninness, Adrian Wills, 2010, 49th IEEE Conference on Decision and Control (CDC).

Prediction Performance After Learning in Gaussian Process Regression

Thomas B. Schön, Petre Stoica, Dave Zachariah, 2017, AISTATS.

Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC

Carl E. Rasmussen, Fredrik Lindsten, Thomas B. Schön, 2013, NIPS.

Sensor Fusion for Augmented Reality

Thomas B. Schön, Fredrik Gustafsson, Jeroen D. Hol, 2006, 2006 9th International Conference on Information Fusion.

Individualised dosing algorithm and personalised treatment of rifampicin for tuberculosis

Thomas B. Schön, Erik Eliasson, Robin J. Svensson, 2019 .

Solving The SLAM Problem for Unmanned Aerial Vehicles Using Smoothed Estimates

Thomas B. Schön, Fredrik Gustafsson, Martin A. Skoglund, 2010 .

Registration by tracking for sequential 2D MRI pdf

Thomas B. Schön, Jens Sjölund, Niklas Gunnarsson, 2020, ArXiv.

Particle Filter SLAM with High Dimensional Vehicle Model

Thomas B. Schön, Fredrik Gustafsson, Rickard Karlsson, 2009, J. Intell. Robotic Syst..

Variational State and Parameter Estimation pdf

Thomas B. Schön, Brett Ninness, Jarrad Courts, 2020, IFAC-PapersOnLine.

Sequential Monte Carlo for Graphical Models

Fredrik Lindsten, Thomas B. Schön, Christian A. Naesseth, 2014, NIPS.

Nonlinear System Identification Using Particle Filters

Thomas B. Schön, Thomas Bo Schön, 2019, Encyclopedia of Systems and Control.

Estimation of linear systems using a Gibbs sampler

Fredrik Lindsten, Thomas B. Schön, Brett Ninness, 2012 .

Robust Point-Mass Filters on Manifolds

Thomas B. Schön, Henrik Tidefelt, 2009 .

Evaluating model calibration in classification

Jacob Roll, Fredrik Lindsten, Thomas B. Schön, 2019, AISTATS.

Indoor Positioning Using Ultrawideband and Inertial Measurements

Thomas B. Schön, Manon Kok, Jeroen D. Hol, 2015, IEEE Transactions on Vehicular Technology.

Navigation and Tracking of Road-Bound Vehicles Using Map Support

Thomas B. Schön, Fredrik Gustafsson, Umut Orguner, 2012 .

Nonlinear state space model identification using a regularized basis function expansion

Thomas B. Schön, Arno Solin, Simo Särkkä, 2015, 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

Sensor Fusion for Augmented Reality

Thomas B. Schön, Fredrik Gustafsson, Jeroen D. Hol, 2008 .

On the Exponential Convergence of the Kaczmarz Algorithm

Thomas B. Schön, Liang Dai, 2015, IEEE Signal Processing Letters.

Automatic Diagnosis of Short-Duration 12-Lead ECG using a Deep Convolutional Network pdf

Thomas B. Schön, Wagner Meira, Derick M. de Oliveira, 2018, ArXiv.

Automatic diagnosis of the 12-lead ECG using a deep neural network

Thomas B. Schön, Manoel Horta Ribeiro, Peter W. Macfarlane, 2020, Nature Communications.

On parameter and state estimation for linear differential-algebraic equations

Lennart Ljung, Thomas B. Schön, Fredrik Gustafsson, 2007, Autom..

Optimistic robust linear quadratic dual control

Thomas B. Schön, Jack Umenberger, 2020, L4DC.

Robust real-time tracking by fusing measurements from inertial and vision sensors

Thomas B. Schön, Fredrik Gustafsson, Jeroen D. Hol, 2007, Journal of Real-Time Image Processing.

Learning to close the loop from 3D point clouds

Thomas B. Schön, Karl Granström, 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Linearly constrained Gaussian processes

Thomas B. Schön, Adrian Wills, Carl Jidling, 2017, NIPS.

Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models pdf

Thomas B. Schön, Marc Peter Deisenroth, Niklas Wahlstrom, 2015, ArXiv.

Modeling magnetic fields using Gaussian processes

Thomas B. Schön, Fredrik Gustafsson, Niklas Wahlstrom, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Fusion of Data from Different Sources

Thomas B. Schön, 2008 .

Parameter Estimation for Discrete-Time Nonlinear Systems Using EM

Thomas B. Schön, Brett Ninness, Adrian Wills, 2008 .

Identification of jump Markov linear models using particle filters

Fredrik Lindsten, Thomas B. Schön, Andreas Svensson, 2014, 53rd IEEE Conference on Decision and Control.

Conditionally Independent Multiresolution Gaussian Processes

Thomas B. Schön, Jalil Taghia, Thomas Bo Schön, 2018, AISTATS.

Autonomous Landing of an Unmanned Aerial Vehicle

Thomas B. Schön, Martin A. Skoglund, Joel Hermansson, 2010 .

Stochastic quasi-Newton with line-search regularization pdf

Thomas B. Schön, Adrian Wills, Thomas Bo Schön, 2019, Autom..

Evaluating the squared-exponential covariance function in Gaussian processes with integral observations pdf

Thomas B. Schön, Adrian Wills, Carl Jidling, 2018, ArXiv.

Online Learning for Distribution-Free Prediction pdf

Thomas B. Schön, Petre Stoica, Dave Zachariah, 2017, ArXiv.

Automatic Diagnosis of the Short-Duration 12-Lead ECG using a Deep Neural Network: the CODE Study pdf

Thomas B. Schön, Wagner Meira, Derick M. de Oliveira, 2019, ArXiv.

Nested Sequential Monte Carlo Methods

Fredrik Lindsten, Thomas B. Schön, C. A. Naesseth, 2015, ICML.

Smoothing With Couplings of Conditional Particle Filters

Fredrik Lindsten, Thomas B. Schön, Pierre E. Jacob, 2017, Journal of the American Statistical Association.

Particle Filter with Rejection Control and Unbiased Estimator of the Marginal Likelihood

Fredrik Lindsten, Thomas B. Schön, Lawrence M. Murray, 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Joint ego-motion and road geometry estimation

Thomas B. Schön, Christian Lundquist, Thomas Bo Schön, 2011, Inf. Fusion.

Pseudo-marginal metropolis light transport

Thomas B. Schön, Jonas Unger, Joel Kronander, 2015, SIGGRAPH Asia Technical Briefs.

Identification of a Duffing oscillator using particle Gibbs with ancestor sampling

Thomas B. Schön, Keith Worden, Elizabeth Cross, 2019, Journal of Physics: Conference Series.

On model order priors for Bayesian identification of SISO linear systems

Thomas B. Schön, Cristian R. Rojas, Patricio E. Valenzuela, 2019, Int. J. Control.

Geo-referencing for UAV navigation using environmental classification

Henrik Ohlsson, Fredrik Lindsten, Thomas B. Schön, 2010, 2010 IEEE International Conference on Robotics and Automation.

Vehicle Motion Estimation Using an Infrared Camera

Jacob Roll, Thomas B. Schön, Christian Lundquist, 2011 .

Estimation of Nonlinear Dynamic Systems : Theory and Applications

Thomas B. Schön, Thomas Bo Schön, 2006 .

Data-Driven Anomaly Detection based on a Bias Change

Thomas B. Schön, André Carvalho Bittencourt, A. C. Bittencourt, 2014 .

Adaptive stopping for fast particle smoothing

Fredrik Lindsten, Thomas B. Schön, Lennart Svensson, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Noise Modeling, State Estimation and System Identification in Linear Differential-Algebraic Equations

Thomas B. Schön, Markus Gerdin, Thomas Bo Schön, 2004 .

Magnetometer Calibration Using Inertial Sensors

Thomas B. Schön, Manon Kok, Thomas Bo Schön, 2016, IEEE Sensors Journal.

Particle-based Gaussian process optimization for input design in nonlinear dynamical models

Johan Dahlin, Thomas B. Schön, Cristian R. Rojas, 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

Real-Time Camera Tracking in the MATRIS Project

Reinhard Koch, Michael Felsberg, Didier Stricker, 2006 .

2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015

Thomas B. Schön, Andreas Svensson, Arno Solin, 2016 .

Detecting spurious features using parity space

Thomas B. Schön, Fredrik Gustafsson, David Törnqvist, 2008, 2008 10th International Conference on Control, Automation, Robotics and Vision.

Parallel Implementation of Particle MCMC Methods on a GPU

Thomas B. Schön, Brett Ninness, Adrian Wills, 2012 .

Navigation and Tracking of Road-Bound Vehicles

Thomas B. Schön, Fredrik Gustafsson, Umut Orguner, 2012 .

Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision

Thomas B. Schön, Martin Danelljan, Fredrik Gustafsson, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo pdf

Fredrik Lindsten, Thomas B. Schön, Andreas Svensson, 2017, ArXiv.

Auxiliary-Particle-Filter-Based Two-Filter Smoothing for Wiener State-Space Models

Thomas B. Schön, Roland Hostettler, Thomas Bo Schön, 2018, 2018 21st International Conference on Information Fusion (FUSION).

Identification of Gaussian Process State-Space Models with Particle Stochastic Approximation EM pdf

Carl E. Rasmussen, Fredrik Lindsten, Thomas B. Schön, 2013, ArXiv.

On robust input design for nonlinear dynamical models

Johan Dahlin, Thomas B. Schön, Cristian R. Rojas, 2017, Autom..

Stochastic quasi-Newton with adaptive step lengths for large-scale problems pdf

Thomas B. Schön, Adrian Wills, 2018, ArXiv.

Gaussian process optimization through sampling from the maximum distribution pdf

Michel Verhaegen, Thomas B. Schön, Jan-Willem van Wingerden, 2016, ArXiv.

Robust ARX Models with Automatic Order Determination and Student's t Innovations

Johan Dahlin, Fredrik Lindsten, Thomas B. Schön, 2011 .

Rao-Blackwellized Particle Smoothers for Conditionally Linear Gaussian Models

Simon J. Godsill, Fredrik Lindsten, Thomas B. Schön, 2015, IEEE Journal of Selected Topics in Signal Processing.

Modeling and Calibration of Inertial and Vision Sensors

Thomas B. Schön, Fredrik Gustafsson, Jeroen D. Hol, 2010, Int. J. Robotics Res..

Second-order particle MCMC for Bayesian parameter inference

Johan Dahlin, Fredrik Lindsten, Thomas B. Schön, 2013 .

Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs

David Broman, Thomas B. Schön, Lawrence M. Murray, 2017, AISTATS.

An optimization-based approach to human body motion capture using inertial sensors

Thomas B. Schön, Manon Kok, Jeroen D. Hol, 2014 .

Hierarchical Bayesian ARX Models for Robust Inference

Johan Dahlin, Fredrik Lindsten, Thomas B. Schön, 2012 .

Deep State Space Models for Nonlinear System Identification pdf

Lennart Ljung, Thomas B. Schön, Niklas Wahlstrom, 2020, IFAC-PapersOnLine.

Learning deep autoregressive models for hierarchical data pdf

Thomas B. Schön, Niklas Wahlstrom, Carl R. Andersson, 2021, IFAC-PapersOnLine.

Latent linear dynamics in spatiotemporal medical data pdf

Thomas B. Schön, Jens Sjölund, Niklas Gunnarsson, 2021, ArXiv.

Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters pdf

Thomas B. Schön, Simon Maskell, Paul R. Horridge, 2021, ArXiv.

Beyond Occam's Razor in System Identification: Double-Descent when Modeling Dynamics pdf

Thomas B. Schön, Adrian Wills, Antônio H. Ribeiro, 2020, IFAC-PapersOnLine.

Data to Controller for Nonlinear Systems: An Approximate Solution

Thomas B. Schön, Brett Ninness, Adrian Wills, 2021, IEEE Control Systems Letters.

CODE-15%: a large scale annotated dataset of 12-lead ECGs

Thomas B. Schön, Manoel Horta Ribeiro, Antônio H. Ribeiro, 2021 .

Pre-trained deep neural network models for age estimation from raw ECG

Thomas B. Schön, Bruce Bartholow Duncan, Manoel Horta Ribeiro, 2021 .

Bayes Control of Hammerstein Systems

Thomas B. Schön, Håkan Hjalmarsson, Mina Ferizbegovic, 2021, IFAC-PapersOnLine.

Learning Proposals for Practical Energy-Based Regression pdf

Thomas B. Schön, Martin Danelljan, Fredrik K. Gustafsson, 2021, AISTATS.

Particle Filter Approach to Nonlinear System Identification under Missing Observations with a Real Application

Thomas B. Schön, R. Bhushan Gopaluni, Adrian Wills, 2009 .

A Modeling and Filtering Framework for Linear Implicit Systems

Thomas B. Schön, Fredrik Gustafsson, Torkel Glad, 2003 .

Online sparse Gaussian process regression using FITC and PITC approximations

Thomas B. Schön, Jan-Willem van Wingerden, Michel Verhaegen, 2015 .

On Identification via EM with Latent Disturbances and Lagrangian Relaxation

Thomas B. Schön, Ian R. Manchester, Jack Umenberger, 2015 .

An Explanation of the Expectation Maximization Algorithm

Thomas B. Schön, Thomas Bo Schön, 2009 .

Particle filtering based identification for autonomous nonlinear ODE models

Thomas B. Schön, Torbjörn Wigren, Bo Bernhardsson, 2015 .

Solving Nonlinear State Estimation Problems Using Particle Filters-An Engineering Perspective

Thomas B. Schön, Thomas Bo Schön, 2010 .