I have written novel research papers published at top conferences and in journals.

I have spent 7+ years pushing the frontiers of human knowledge within fields such as AI/Machine learning, Computer Graphics, Computational Statistics, System Identification, and more.

Journal papers

Getting started with particle Metropolis-Hastings for inference in nonlinear dynamical models.

J. Dahlin and T. B. Schön.

Journal of Statistical Software, Foundation for Open Access Statistics, 2015.
pre-print (pdf) code

On robust input design for nonlinear dynamical models.

P. E. Valenzuela, J. Dahlin, C. R. Rojas and T. B. Schön.

Automatica, Volume 77, pp 268-278, Elseiver, 2017.
journal version

Particle Metropolis-Hastings using gradient and Hessian information.

J. Dahlin and T. B. Schön.

Statistics and Computing, Volume 25, Issue 1, pp 81-92, Springer, 2015.
pre-print (pdf) journal version code

Conference papers

Real-Time Robotic Search using Structural Spatial Point Processes.

O. Andersson, P. Sidén, J. Dahlin, P. Doherty and M. Villani.

Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR, Virtual, August 2020.
conference version

Accurate Gaussian mixture model smoothing using a two-filter approach.

M. Balenzuela, J. Dahlin, N. Bartlett, A. Wills, C. Renton and B. Ninness.

Proceedings of the 57th IEEE Conference on Decision and Control, Miami Beach, FL, USA, December 2018.
conference version

Constructing Metropolis-Hastings proposals using damped BFGS updates.

J. Dahlin, A. Wills and B. Ninness.

Proceedings of the 18th IFAC Symposium on System Identification, Stockholm, Sweden, July 2018.
pre-print (pdf) code

Sparse Bayesian ARX models with flexible noise distributions.

J. Dahlin, A. Wills and B. Ninness.

Proceedings of the 18th IFAC Symposium on System Identification, Stockholm, Sweden, July 2018.
pre-print (pdf) code

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

P.E. Valenzuela, J. Dahlin, C. R. Rojas and T.B. Schön.

Proceedings of the 55th Conference of Decision and Control (CDC), Las Vegas, USA, December 2016.
pre-print (pdf)

Marginalizing Gaussian Process Hyperparameters using Sequential Monte Carlo.

A. Svensson, J. Dahlin and T. B. Schön.

Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Cancun, Mexico, December 2015.
pre-print (pdf) code

Sequential Monte Carlo Methods for System Identification.

T. B. Schön, F. Lindsten, J. Dahlin, J. Wågberg, C. A. Naesseth, A. Svensson and L. Dai.

Proceedings of the 17th IFAC Symposium on System Identification, Beijing, China, October 2015.
pre-print (pdf) conference version code

Newton-based maximum likelihood estimation in nonlinear state space models.

M. Kok, J. Dahlin, T. B. Schön and A. Wills.

Proceedings of the 17th IFAC Symposium on System Identification, Beijing, China, October 2015.
pre-print (pdf) conference version code

Quasi-Newton particle Metropolis-Hastings.

J. Dahlin, F. Lindsten and T. B. Schön.

Proceedings of the 17th IFAC Symposium on System Identification, Beijing, China, October 2015.
pre-print (pdf) conference version code

Real-time Video Based Lighting Using GPU Raytracing.

J. Kronander, J. Dahlin, D. Jönsson, M. Kok, T. B. Schön and J. Unger.

Proceedings of the 2014 European Signal Processing Conference (EUSIPCO), Lisbon, Portugal, September 2014.
pre-print (pdf) conference version

Backward sequential Monte Carlo for marginal smoothing.

J. Kronander, T. B. Schön and J. Dahlin.

Proceedings of the 2014 IEEE Statistical Signal Processing Workshop (SSP), Gold Coast, Australia, July 2014.
pre-print (pdf) conference version

Detection and positioning of overtaking vehicles using 1D optical flow.

D. Hultqvist, J. Roll, F. Svensson, J. Dahlin and T. B. Schön.

Proceedings of the IEEE Intelligent Vehicles (IV) Symposium, Dearborn, MI, USA, June 2014.
pre-print (pdf) conference version

Second-order particle MCMC for Bayesian parameter inference.

J. Dahlin, F. Lindsten and T. B. Schön.

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

Particle filter-based Gaussian process optimisation for parameter inference.

J. Dahlin and F. Lindsten.

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

A graph/particle-based method for experiment design in nonlinear systems.

P. E. Valenzuela, J. Dahlin. C. R. Rojas and T. B. Schön.

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

Particle Metropolis Hastings using Langevin Dynamics.

J. Dahlin, F. Lindsten and T. B. Schön.

Proceedings of the 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 2013.
pre-print (pdf) conference version code

Combining Entity Matching Techniques for Detecting Extremist Behavior on Discussion Boards.

J. Dahlin, F. Johansson, L. Kaati, C. Mårtensson and P. Svenson.

Proceedings of International Symposium on Foundation of Open Source Intelligence and Security Informatics 2012, Istanbul, Turkey, August 2012.
pre-print (pdf) conference version

Hierarchical Bayesian approaches for robust inference in ARX models.

J. Dahlin, F. Lindsten, T. B. Schön and A. Wills.

Proceedings of the 16th IFAC Symposium on System Identification, Brussels, Belgium, July 2012.
pre-print (pdf) conference version code

A Method for Community Detection in Uncertain Networks.

J. Dahlin and P. Svenson.

Proceedings of 2011 European Intelligence and Security Informatics Conference, Athens, Greece, August 2011.
pre-print (pdf) conference version

Theses

Accelerating Monte Carlo methods for Bayesian inference in dynamical models.

J. Dahlin.

Linköping Studies in Science and Technology. Dissertations. No. 1754, 2016.
full text (pdf) DiVA code

Sequential Monte Carlo for inference in nonlinear state space models.

J. Dahlin.

Linköping Studies in Science and Technology. Thesis. No. 1652, 2014.
full text (pdf) DiVA code

Community Detection in Imperfect Networks.

J. Dahlin.

Student Thesis at Umeå University, 2011.
full text (pdf) DiVA

Simulated Double Auction-markets with production and storage.

J. Dahlin.

Student Thesis at Umeå University, 2011.
full text (pdf)

Technical Reports (Not published elsewhere

Practical Bayesian System Identification using Hamiltonian Monte Carlo.

J. Hendriks, A. Willis, B. Ninness and J. Dahlin.

arXiv:2011.04117, November 2020.
pre-print (pdf)

Approximate Bayesian inference for mixed effects models with heterogeneity.

J. Dahlin, R. Kohn and T. B. Schön.

Technical report LiTH-ISY-R-3091, Department of Electrical Engineering, Linköping University, March 2016.
pre-print (pdf) code

Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables.

J. Dahlin, F. Lindsten, J. Kronander and T. B. Schön.

arXiv:1511.05483, November 2015.
pre-print (pdf) code

Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods.

J. Dahlin, M. Villani and T. B. Schön.

arXiv:1506.06975, June 2017.
pre-print (pdf) code

Ensemble approaches for improving community detection methods.

J. Dahlin, and P. Svenson.

arXiv:1309.0242, September 2013.
pre-print (pdf)

Inference in Gaussian models with missing data using Equalisation Maximisation.

J. Dahlin, F. Lindsten and T. B. Schön.

arXiv:1308.4601, August 2013.
pre-print (pdf)

Entity matching.

J. Dahlin.

Technical Report at Swedish Defence Research Agency, FOI-R-3265-SE, August 2012.