Publications

The page lists my publications both published and current work, see Google Scholar for citation information.
BibTeX citations for most of my publications are available in this file.

Journal contributions

[J3] J. Dahlin and T. B. Schön, Getting started with particle Metropolis-Hastings for inference in nonlinear dynamical models
Journal of Statistical Software
, Code Snippets, Volume 88, Number 2, pp. 1-41, Foundation for Open Access Statistics, 2019.
open access journal edition (pdf) | code@GitHub ]

[J2] P. E. Valenzuela, J. Dahlin, C. R. Rojas and T. B. Schön, On robust input design for nonlinear dynamical models.
Automatica, Volume 77, pp 268-278, Elseiver, 2017.
journal version ]

[J1] J. Dahlin, F. Lindsten and T. B. Schön, Particle Metropolis-Hastings using gradient and Hessian information.
Statistics and Computing, Volume 25, Issue 1, pp 81-92, Springer, 2015.
pre-print (pdf) | journal version | code@GitHub ]

Conference contributions

[C19] O. Andersson, P. Sidén, J. Dahlin, P. Doherty and M. Villani, Real-Real-Time Robotic Search using Structural Spatial Point Processes.
Proceedings of the conference on Uncertainty in Artificial Intelligence (UAI), Tel Aviv, Israel, July 2019.
[ conference version (pdf) ]

[C18] M. Balenzuela, J. Dahlin, N. Bartlett, A. Wills, C. Renton and B. Ninness, Accurate Gaussian mixture model smoothing using a two-filter approach.
Proceedings of the 57th IEEE Conference on Decision and Control, Miami Beach, FL, USA, December 2018.

[C17] J. Dahlin, A. Wills and B. Ninness, Constructing Metropolis-Hastings proposals using damped BFGS updates.
Accepted for the Proceedings of the 18th IFAC Symposium on System Identification, Stockholm, Sweden, July 2018.
pre-print (pdf) | code@GitHub ]

[C16] J. Dahlin, A. Wills and B. Ninness, Sparse Bayesian ARX models with flexible noise distributions.
Accepted for the Proceedings of the 18th IFAC Symposium on System Identification, Stockholm, Sweden, July 2018.
pre-print (pdf) | code@GitHub ]

[C15] P.E. Valenzuela, J. Dahlin, C. R. Rojas and T.B. Schön, Particle-based Gaussian process optimization for input design in nonlinear dynamical models.
Proceedings of the 55th Conference of Decision and Control (CDC), Las Vegas, USA, December 2016.
pre-print (pdf) ]

[C14] A. Svensson, J. Dahlin and T. B. Schön, Marginalizing Gaussian Process Hyperparameters using Sequential Monte Carlo.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Cancun, Mexico, December 2015.
extended pre-print (pdf) | code ]

[C13] T. B. Schön, F. Lindsten, J. Dahlin, J. Wågberg, C. A. Naesseth, A. Svensson and L. Dai, Sequential Monte Carlo Methods for System Identification.
Proceedings of the 17th IFAC Symposium on System Identification, Beijing, China, October 2015.
pre-print (pdf) | conference version | code ]

[C12] M. Kok, J. Dahlin, T. B. Schön and A. Wills, Newton-based maximum likelihood estimation in nonlinear state space models.
Proceedings of the 17th IFAC Symposium on System Identification, Beijing, China, October 2015.
pre-print (pdf) | conference version | code@GitHub ]

[C11] J. Dahlin, F. Lindsten and T. B. Schön, Quasi-Newton particle Metropolis-Hastings.
Proceedings of the 17th IFAC Symposium on System Identification, Beijing, China, October 2015.
pre-print (pdf) | conference version | code@GitHub ]

[C10] J. Kronander, J. Dahlin, D. Jönsson, M. Kok, T. B. Schön and J. Unger. Real-time Video Based Lighting Using GPU Raytracing.
Proceedings of the 2014 European Signal Processing Conference (EUSIPCO), Lisbon, Portugal, September 2014.
pre-print (pdf) | conference version ]

[C9] J. Kronander, T. B. Schön and J. Dahlin. Backward sequential Monte Carlo for marginal smoothing.
Proceedings of the 2014 IEEE Statistical Signal Processing Workshop (SSP), Gold Coast, Australia, July 2014.
pre-print (pdf) | conference version ]

[C8] D. Hultqvist, J. Roll, F. Svensson, J. Dahlin and T. B. Schön. Detection and positioning of overtaking vehicles using 1D optical flow.
Proceedings of the IEEE Intelligent Vehicles (IV) Symposium, Dearborn, MI, USA, June 2014.
pre-print (pdf) | conference version ]

[C7] J. Dahlin, F. Lindsten and T. B. Schön, Second-order particle MCMC for Bayesian parameter inference.
Proceedings of the 19th World Congress of the International Federation of Automatic Control (IFAC), Cape Town, South Africa, August 2014.
pre-print (pdf) | conference version | code@GitHub ]

[C6] J. Dahlin and F. Lindsten, Particle filter-based Gaussian process optimisation for parameter inference.
Proceedings of the 19th World Congress of the International Federation of Automatic Control (IFAC), Cape Town, South Africa, August 2014.
pre-print (pdf) | conference version | code@GitHub ]

[C5] P. E. Valenzuela, J. Dahlin. C. R. Rojas and T. B. Schön, A graph/particle-based method for experiment design in nonlinear systems.
Proceedings of the 19th World Congress of the International Federation of Automatic Control (IFAC), Cape Town, South Africa, August 2014.
pre-print (pdf) | conference version ]

[C4] J. Dahlin, F. Lindsten and T. B. Schön, Particle Metropolis Hastings using Langevin Dynamics.
Proceedings of the 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 2013.
pre-print (pdf) | conference version | code@GitHub ]

[C3] J. Dahlin, F. Johansson, L. Kaati, C. Mårtensson and P. Svenson, Combining Entity Matching Techniques for Detecting Extremist Behavior on Discussion Boards.
Proceedings of International Symposium on Foundation of Open Source Intelligence and Security Informatics 2012, Istanbul, Turkey, August 2012.
pre-print (pdf) | conference version ]

[C2] J. Dahlin, F. Lindsten, T. B. Schön and A. Wills, Hierarchical Bayesian approaches for robust inference in ARX models.
Proceedings of the 16th IFAC Symposium on System Identification, Brussels, Belgium, July 2012.
pre-print (pdf) | conference version | code@GitHub ]

[C1] J. Dahlin and P. Svenson, A Method for Community Detection in Uncertain Networks.
Proceedings of 2011 European Intelligence and Security Informatics Conference, Athens, Greece, August 2011.
pre-print (pdf) | conference version ]

Theses

[PhD1] J. Dahlin, Accelerating Monte Carlo methods for Bayesian inference in dynamical models.
Linköping Studies in Science and Technology. Dissertations. No. 1754, 2016.
full text (pdf) | DiVA | code@GitHub ] 

[Lic1] J. Dahlin, Sequential Monte Carlo for inference in nonlinear state space models
Linköping Studies in Science and Technology. Thesis. No. 1652, 2014.
full text (pdf) | DiVA | code@GitHub ] 

[MSc1] J. Dahlin, Community Detection in Imperfect Networks
Student Thesis at Umeå University, 2011.
full text (pdf) | DiVA ] 

[BSc1] J. Dahlin, Simulated Double Auction-markets with production and storage
Student Thesis at Umeå University, 2011.
full text (pdf) ]

Technical Reports (Not published elsewhere)

[RT7] J. Dahlin, A. Wills  and B. Ninness, Correlated pseudo-marginal Metropolis-Hastings using quasi-Newton proposals.
arXiv:1806.09780, June 2018.
pre-print (pdf) | code@GitHub ]

[TR6] J. Dahlin, R. Kohn and T. B. Schön, Approximate Bayesian inference for mixed effects models with heterogeneity.
Technical report LiTH-ISY-R-3091, Department of Electrical Engineering, Linköping University, March 2016.
pre-print (pdf)  | code@GitHub ]

[TR5] J. Dahlin, F. Lindsten, J. Kronander and T. B. Schön, Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables.
arXiv:1511.05483, November 2015.
pre-print (pdf)  | code@GitHub ]

[TR4] J. Dahlin, M. Villani and T. B. Schön, Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods.
arXiv:1506.06975, June 2017.
pre-print (pdf) | code@GitHub ]

[TR3] J. Dahlin, and P. Svenson, Ensemble approaches for improving community detection methods.
arXiv:1309.0242, September 2013.
pre-print (pdf) ]

[TR2] J. Dahlin, F. Lindsten and T. B. Schön, Inference in Gaussian models with missing data using Equalisation Maximisation.
arXiv:1308.4601, August 2013.
[pre-print (pdf) ]

[TR1] J. Dahlin, Entity matching.
Technical Report at Swedish Defence Research Agency, FOI-R-3265-SE, August 2012.
[full text (pdf) ]