Thomas B. Schön

According to our database1, Thomas B. Schön authored at least 123 papers between 2003 and 2020.

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

Timeline

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Bibliography

2020
Nonlinear Input Design as Optimal Control of a Hamiltonian System.
IEEE Control Systems Letters, 2020

Learning Robust LQ-Controllers Using Application Oriented Exploration.
IEEE Control Systems Letters, 2020

Constructing a variational family for nonlinear state-space models.
CoRR, 2020

Linearly Constrained Neural Networks.
CoRR, 2020

2019
High-Dimensional Filtering Using Nested Sequential Monte Carlo.
IEEE Trans. Signal Processing, 2019

A Fast and Robust Algorithm for Orientation Estimation Using Inertial Sensors.
IEEE Signal Process. Lett., 2019

On model order priors for Bayesian identification of SISO linear systems.
Int. J. Control, 2019

Elements of Sequential Monte Carlo.
Foundations and Trends in Machine Learning, 2019

Optimistic robust linear quadratic dual control.
CoRR, 2019

DCTD: Deep Conditional Target Densities for Accurate Regression.
CoRR, 2019

Deep kernel learning for integral measurements.
CoRR, 2019

Deep Convolutional Networks in System Identification.
CoRR, 2019

Stochastic quasi-Newton with line-search regularization.
CoRR, 2019

The trade-off between long-term memory and smoothness for recurrent networks.
CoRR, 2019

Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision.
CoRR, 2019

On the Smoothness of Nonlinear System Identification.
CoRR, 2019

Automatic Diagnosis of the Short-Duration 12-Lead ECG using a Deep Neural Network: the CODE Study.
CoRR, 2019

Constructing the Matrix Multilayer Perceptron and its Application to the VAE.
CoRR, 2019

Optimal controller/observer gains of discounted-cost LQG systems.
Automatica, 2019

Data Consistency Approach to Model Validation.
IEEE Access, 2019

Probabilistic Programming for Birth-Death Models of Evolution Using an Alive Particle Filter with Delayed Sampling.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Robust exploration in linear quadratic reinforcement learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding.
Proceedings of the 36th International Conference on Machine Learning, 2019

Evaluating model calibration in classification.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Conditionally Independent Multiresolution Gaussian Processes.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

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

Evaluating the squared-exponential covariance function in Gaussian processes with integral observations.
CoRR, 2018

Automatic Diagnosis of Short-Duration 12-Lead ECG using a Deep Convolutional Network.
CoRR, 2018

A fast quasi-Newton-type method for large-scale stochastic optimisation.
CoRR, 2018

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

Stochastic quasi-Newton with adaptive step lengths for large-scale problems.
CoRR, 2018

Data-Driven Impulse Response Regularization via Deep Learning.
CoRR, 2018

Maximum likelihood identification of stable linear dynamical systems.
Automatica, 2018

Automated learning with a probabilistic programming language: Birch.
Annual Reviews in Control, 2018

Learning convex bounds for linear quadratic control policy synthesis.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Localized Spatio-Temporal Models From Streaming Data.
Proceedings of the 35th International Conference on Machine Learning, 2018

Auxiliary-Particle-Filter-Based Two-Filter Smoothing for Wiener State-Space Models.
Proceedings of the 21st International Conference on Information Fusion, 2018

Regularized parametric system identification: a decision-theoretic formulation.
Proceedings of the 2018 Annual American Control Conference, 2018

Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Using Inertial Sensors for Position and Orientation Estimation.
Foundations and Trends in Signal Processing, 2017

How consistent is my model with the data? Information-Theoretic Model Check.
CoRR, 2017

Learning nonlinear state-space models using smooth particle-filter-based likelihood approximations.
CoRR, 2017

Online Learning for Distribution-Free Prediction.
CoRR, 2017

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo.
CoRR, 2017

On robust input design for nonlinear dynamical models.
Automatica, 2017

A flexible state-space model for learning nonlinear dynamical systems.
Automatica, 2017

Linearly constrained Gaussian processes.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

On the construction of probabilistic Newton-type algorithms.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

Prediction Performance After Learning in Gaussian Process Regression.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Using Convolution to Estimate the Score Function for Intractable State-Transition Models.
IEEE Signal Process. Lett., 2016

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

Linear System Identification via EM with Latent Disturbances and Lagrangian Relaxation.
CoRR, 2016

Magnetometer calibration using inertial sensors.
CoRR, 2016

A Scalable and Distributed Solution to the Inertial Motion Capture Problem.
CoRR, 2016

Gaussian process optimization through sampling from the maximum distribution.
CoRR, 2016

Online Sparse Gaussian Process Training with Input Noise.
CoRR, 2016

Mean and variance of the LQG cost function.
Automatica, 2016

Accelerometer calibration using sensor fusion with a gyroscope.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Particle-based Gaussian process optimization for input design in nonlinear dynamical models.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

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

2015
Nonlinear System Identification Using Particle Filters.
Proceedings of the Encyclopedia of Systems and Control, 2015

Indoor Positioning Using Ultrawideband and Inertial Measurements.
IEEE Trans. Vehicular Technology, 2015

A New Structure Exploiting Derivation of Recursive Direct Weight Optimization.
IEEE Trans. Automat. Contr., 2015

On the Exponential Convergence of the Kaczmarz Algorithm.
IEEE Signal Process. Lett., 2015

Particle Metropolis-Hastings using gradient and Hessian information.
Statistics and Computing, 2015

From Pixels to Torques: Policy Learning with Deep Dynamical Models.
CoRR, 2015

Nonlinear state space smoothing using the conditional particle filter.
CoRR, 2015

Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models.
CoRR, 2015

Pseudo-marginal metropolis light transport.
Proceedings of the SIGGRAPH Asia 2015 Technical Briefs, Kobe, Japan, November 2-6, 2015, 2015

Nested Sequential Monte Carlo Methods.
Proceedings of the 32nd International Conference on Machine Learning, 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

Marginalizing Gaussian process hyperparameters using sequential Monte Carlo.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

2014
Particle gibbs with ancestor sampling.
J. Mach. Learn. Res., 2014

Learning deep dynamical models from image pixels.
CoRR, 2014

Backward sequential Monte Carlo for marginal smoothing.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Robust auxiliary particle filters using multiple importance sampling.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Sequential Monte Carlo for Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Detecting and positioning overtaking vehicles using 1D optical flow.
Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

Capacity estimation of two-dimensional channels using Sequential Monte Carlo.
Proceedings of the 2014 IEEE Information Theory Workshop, 2014

Real-time video based lighting using GPU raytracing.
Proceedings of the 22nd European Signal Processing Conference, 2014

Identification of jump Markov linear models using particle filters.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2013
Backward Simulation Methods for Monte Carlo Statistical Inference.
Foundations and Trends in Machine Learning, 2013

Identification of Gaussian Process State-Space Models with Particle Stochastic Approximation EM.
CoRR, 2013

Identification of Hammerstein-Wiener models.
Automatica, 2013

Bayesian semiparametric Wiener system identification.
Automatica, 2013

Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Modeling magnetic fields using Gaussian processes.
Proceedings of the IEEE International Conference on Acoustics, 2013

Adaptive stopping for fast particle smoothing.
Proceedings of the IEEE International Conference on Acoustics, 2013

Rao-Blackwellized particle smoothers for mixed linear/nonlinear state-space models.
Proceedings of the IEEE International Conference on Acoustics, 2013

MEMS-based inertial navigation based on a magnetic field map.
Proceedings of the IEEE International Conference on Acoustics, 2013

Particle metropolis hastings using Langevin dynamics.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Ancestor Sampling for Particle Gibbs.
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

On the use of backward simulation in the particle Gibbs sampler.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Calibration of a magnetometer in combination with inertial sensors.
Proceedings of the 15th International Conference on Information Fusion, 2012

On mixture reduction for multiple target tracking.
Proceedings of the 15th International Conference on Information Fusion, 2012

2011
A General Convergence Result for Particle Filtering.
IEEE Trans. Signal Processing, 2011

Decentralized Particle Filter With Arbitrary State Decomposition.
IEEE Trans. Signal Processing, 2011

Joint ego-motion and road geometry estimation.
Information Fusion, 2011

Learning to close loops from range data.
I. J. Robotics Res., 2011

System identification of nonlinear state-space models.
Automatica, 2011

Bicycle tracking using ellipse extraction.
Proceedings of the 14th International Conference on Information Fusion, 2011

2010
Modeling and Calibration of Inertial and Vision Sensors.
I. J. Robotics Res., 2010

Learning to close the loop from 3D point clouds.
Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

Geo-referencing for UAV navigation using environmental classification.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010

Torchlight Navigation.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

Estimating state-space models in innovations form using the expectation maximisation algorithm.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Estimation of general nonlinear state-space systems.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Identification of mixed linear/nonlinear state-space models.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Decentralization of particle filters using arbitrary state decomposition.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

2009
Particle Filter SLAM with High Dimensional Vehicle Model.
Journal of Intelligent and Robotic Systems, 2009

Experimental comparison of observers for tool position estimation of industrial robots.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009

2008
A Basic Convergence Result for Particle Filtering.
IEEE Trans. Signal Processing, 2008

Relative pose calibration of a spherical camera and an IMU.
Proceedings of the 7th IEEE and ACM International Symposium on Mixed and Augmented Reality, 2008

Detecting spurious features using parity space.
Proceedings of the 10th International Conference on Control, 2008

A new algorithm for calibrating a combined camera and IMU sensor unit.
Proceedings of the 10th International Conference on Control, 2008

2007
Robust real-time tracking by fusing measurements from inertial and vision sensors.
J. Real-Time Image Processing, 2007

On parameter and state estimation for linear differential-algebraic equations.
Automatica, 2007

A framework for simultaneous localization and mapping utilizing model structure.
Proceedings of the 10th International Conference on Information Fusion, 2007

Fast particle filters for multi-rate sensors.
Proceedings of the 15th European Signal Processing Conference, 2007

A robust particle filter for state estimation - with convergence results.
Proceedings of the 46th IEEE Conference on Decision and Control, 2007

2006
Sensor Fusion for Augmented Reality.
Proceedings of the 9th International Conference on Information Fusion, 2006

2005
Marginalized particle filters for mixed linear/nonlinear state-space models.
IEEE Trans. Signal Processing, 2005

2003
A note on state estimation as a convex optimization problem.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003


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