Johan Dahlin

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	All	Since 2016
Citations	388	274
h-index	12	9
i10-index	15	9

20122013201420152016201720182019202020214 8 36 56 55 51 62 58 36 9

Co-authors

Thomas SchönProfessor, Uppsala UniversityVerified email at it.uu.se
Fredrik LindstenAssociate Professor, Linköping UniversityVerified email at liu.se
Adrian WillsUniversity of Newcastle AustraliaVerified email at newcastle.edu.au
Pontus SvensonRISE SICSVerified email at ri.se
Andreas Lindholm (Svensson)Machine Learning Research Engineer, AnnotellVerified email at annotell.com
Joel KronanderComputer Vision/Machine Learning at NinesVerified email at liu.se
B NinnessUniversity of Newcastle AustraliaVerified email at newcastle.edu.au
Mattias VillaniProfessor of Statistics, Stockholm University and Linköping UniversityVerified email at stat.su.se
Cristian R. RojasAssociate Professor, Division of Decision and Control Systems, KTH Royal Institute of TechnologyVerified email at ee.kth.se
Christian A. NaessethPostdoctoral Research Scientist at Columbia UniversityVerified email at columbia.edu
Manon KokAssistant Professor at the Delft Center for Systems and ControlVerified email at tudelft.nl
Christian MårtensonFOIVerified email at foi.se
Fredrik JohanssonSenior Scientist @ Swedish Defence Research Agency (FOI)Verified email at foi.se
Lisa KaatiSenior scientist and group leader, FOIVerified email at foi.se
Daniel JönssonLinköping UniversityVerified email at liu.se
Jonas UngerProfessor, division for Media and Information Technology, Linköping University, SwedenVerified email at liu.se
robert kohnProfessor of Economics University of New South WalesVerified email at unsw.edu.au
Liang Dai（戴亮）
Liang DaiUniversity of California, BerkeleyVerified email at berkeley.edu

Johan Dahlin

Head of Product, AgriOpt AB, Stockholm, Sweden

Verified email at johandahlin.com - Homepage

Bayesian Learning Computational Statistics Machine Learning Monte Carlo Methods System Identification


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Sequential Monte Carlo Methods for System Identification TB Schön, F Lindsten, J Dahlin, J Wågberg, CA Naesseth, A Svensson, ... IFAC-PapersOnLine 48 (28), 775-786, 2015	62	2015
Particle Metropolis–Hastings using gradient and Hessian information J Dahlin, F Lindsten, TB Schön Statistics and computing 25 (1), 81-92, 2015	44	2015
Ensemble approaches for improving community detection methods J Dahlin, P Svenson arXiv preprint arXiv:1309.0242, 2013	28	2013
Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables J Dahlin, F Lindsten, J Kronander, TB Schön arXiv preprint arXiv:1511.05483, 2015	25	2015
Combining entity matching techniques for detecting extremist behavior on discussion boards J Dahlin, F Johansson, L Kaati, C Mårtenson, P Svenson 2012 IEEE/ACM International Conference on Advances in Social Networks …, 2012	22	2012
Detecting and positioning overtaking vehicles using 1D optical flow D Hultqvist, J Roll, F Svensson, J Dahlin, TB Schön 2014 IEEE Intelligent Vehicles Symposium Proceedings, 861-866, 2014	19	2014
Particle filter-based Gaussian process optimisation for parameter inference J Dahlin, F Lindsten IFAC Proceedings Volumes 47 (3), 8675-8680, 2014	18	2014
A method for community detection in uncertain networks J Dahlin, P Svenson 2011 European Intelligence and Security Informatics Conference, 155-162, 2011	18	2011
Marginalizing Gaussian process hyperparameters using sequential Monte Carlo A Svensson, J Dahlin, TB Schön 2015 IEEE 6th International Workshop on Computational Advances in Multi …, 2015	13	2015
Particle Metropolis Hastings using Langevin dynamics J Dahlin, F Lindsten, T Schon Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International …, 2013	13	2013
Newton-based maximum likelihood estimation in nonlinear state space models M Kok, J Dahlin, TB Schön, A Wills IFAC-PapersOnLine 48 (28), 398-403, 2015	12	2015
Second-order particle MCMC for Bayesian parameter inference J Dahlin, F Lindsten, TB Schön IFAC Proceedings Volumes 47 (3), 8656-8661, 2014	12	2014
Hierarchical Bayesian ARX models for robust inference J Dahlin, F Lindsten, TB Schön, A Wills System Identification 16 (1), 131-136, 2012	12	2012
Quasi-Newton particle Metropolis-Hastings J Dahlin, F Lindsten, TB Schön IFAC-PapersOnLine 48 (28), 981-986, 2015	11	2015
Getting started with particle Metropolis-Hastings for inference in nonlinear dynamical models J Dahlin, TB Schön arXiv preprint arXiv:1511.01707, 2015	10	2015
Real-time video based lighting using GPU raytracing J Kronander, J Dahlin, D Jönsson, M Kok, TB Schön, J Unger 2014 22nd European Signal Processing Conference (EUSIPCO), 1627-1631, 2014	8	2014
A graph/particle-based method for experiment design in nonlinear systems PE Valenzuela, J Dahlin, CR Rojas, TB Schön IFAC Proceedings Volumes 47 (3), 1404-1409, 2014	8	2014
Getting started with particle Metropolis-Hastings for inference in nonlinear dynamical models J Dahlin, TB Schön Journal of Statistical Software 88 (CN2), 1-41, 2019	6	2019
Sparse Bayesian ARX models with flexible noise distributions J Dahlin, A Wills, B Ninness IFAC-PapersOnLine 51 (15), 25-30, 2018	6	2018
On robust input design for nonlinear dynamical models PE Valenzuela, J Dahlin, CR Rojas, TB Schön Automatica 77, 268-278, 2017	6	2017

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