Department of Information Technology

Publications

Journal papers

[J3] Thomas B. Schön, Andreas Svensson, Lawrence Murray and Fredrik Lindsten, Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo. Accepted for publication in Mechanical Systems and Signal Processing. Pre-print on arXiv.org. Code.

[J2] Andreas Svensson, Thomas B. Schön, Fredrik Lindsten, Learning of state-space models with highly informative observations: a tempered Sequential Monte Carlo solution. Accepted for publication in Mechanical Systems and Signal Processing. Pre-print on arXiv.org. Code.

[J1] Andreas Svensson, Thomas B. Schön, A flexible state space model for learning nonlinear dynamical systems. Automatica 80 (2017), page 189-199. ScienceDirect. arXiv.org (pre-print). Code is available at this page.

Conference papers

[C6] Andreas Svensson, Arno Solin, Simo Särkkä, Thomas B. Schön, Computationally Efficient Bayesian Learning of Gaussian Process State Space Models. In proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), Cadiz, Spain, May 2016, page 213-221. JMLR, arXiv.org. Material is available here.

[C5] Andreas Svensson, Thomas B. Schön, Arno Solin, Simo Särkkä, Nonlinear State Space Model Identification Using a Regularized Basis Function Expansion. In proceedings of the 6th IEEE international workshop on computational advances in multi-sensor adaptive processing (CAMSAP), Cancun, Mexico, December 2015, page 481-484. Pre-print on arXiv.org. Matlab code, posters etc. IEEE Xplore

[C4] Andreas Svensson, Johan Dahlin, Thomas B. Schön. Marginalizing Gaussian Process Hyperparameters using Sequential Monte Carlo. In proceedings of the 6th IEEE international workshop on computational advances in multi-sensor adaptive processing (CAMSAP), Cancun, Mexico, December 2015, page 477-480. Pre-print on arXiv.org. Matlab code and data. Poster. IEEE Xplore

[C3] Andreas Svensson, Thomas B. Schön, Manon Kok, Nonlinear state space smoothing using the conditional particle filter. In Proceedings of 17th IFAC Symposium on System Identification (SYSID), Beijing, China, October, 2015, pre-print on arXiv.org. Matlab code. Presentation. ScienceDirect.

[C2] Thomas B. Schön, Fredrik Lindsten, Johan Dahlin, Johan Wågberg, Christian A. Naesseth, Andreas Svensson and Liang Dai, Sequential Monte Carlo Methods for System Identification. In Proceedings of 17th IFAC Symposium on System Identification (SYSID), Beijing, China, October, 2015, pre-print on arXiv.org. ScienceDirect.

[C1] Andreas Svensson, Thomas B. Schön and Fredrik Lindsten, Identification of jump Markov linear models using particle filters. In Proceedings of 53rd IEEE Conference on Decision and Control (CDC), Los Angeles, CA, USA, December, 2014. IEEE Xplore, arXiv.org, PDF. Code, presentation, poster etc.

Technical reports

[TR3] Andreas Svensson, On the Role of Monte Carlo Methods in Swedish M. Sc. Engineering Education. Department of Information Technology, Uppsala University, Technical Report 2016-009.

[TR2] Andreas Svensson, Thomas B. Schön, Comparing Two Recent Particle Filter Implementations of Bayesian System Identification. Department of Information Technology, Uppsala University, Technical Report 2016-008. Presented at Reglermöte 2016. Code available.

[TR1] Andreas Svensson, Thomas B. Schön, Manon Kok, Some details on state space smoothing using the conditional particle filter. Department of Information Technology, Uppsala University, Technical Report 2015-019.

Theses

[Lic] Andreas Svensson, Learning probabilistic models of dynamical
phenomena using particle filters. Licentiate thesis. PDF.


[MSc] Andreas Svensson, Model Predictive Control with Invariant Sets in Artificial Pancreas for Type 1 Diabetes Mellitus, Department of Electrical Engineering, Linköping University, 2013. LiTH-ISY-EX--13/4699--SE, available in DiVA.

[BSc] Andreas Svensson, Automatic Generation of Control Code for Flexible Automation, Department of Electrical Engineering, Linköping University, 2012. LiTH-ISY-EX-ET--12/0400--SE, available in DiVA.

Updated  2017-10-23 08:56:18 by Andreas Svensson.