Följ
Johan Dahlin
Johan Dahlin
Kotte Consulting AB, Stockholm, Sweden
Verifierad e-postadress på johandahlin.com
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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
1032015
Particle Metropolis–Hastings using gradient and Hessian information
J Dahlin, F Lindsten, TB Schön
Statistics and computing 25, 81-92, 2015
552015
Ensemble approaches for improving community detection methods
J Dahlin, P Svenson
arXiv preprint arXiv:1309.0242, 2013
362013
Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables
J Dahlin, F Lindsten, J Kronander, TB Schön
arXiv preprint arXiv:1511.05483, 2015
322015
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
262012
Particle filter-based Gaussian process optimisation for parameter inference
J Dahlin, F Lindsten
IFAC Proceedings Volumes 47 (3), 8675-8680, 2014
222014
A method for community detection in uncertain networks
J Dahlin, P Svenson
2011 European Intelligence and Security Informatics Conference, 155-162, 2011
222011
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
202014
Getting started with particle Metropolis-Hastings for inference in nonlinear dynamical models
J Dahlin, TB Schön
Journal of Statistical Software 88, 1-41, 2019
192019
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
192015
Particle Metropolis Hastings using Langevin dynamics
J Dahlin, F Lindsten, T Schon
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International …, 2013
162013
Second-order particle MCMC for Bayesian parameter inference
J Dahlin, F Lindsten, TB Schön
IFAC Proceedings Volumes 47 (3), 8656-8661, 2014
152014
Sparse Bayesian ARX models with flexible noise distributions
J Dahlin, A Wills, B Ninness
IFAC-PapersOnLine 51 (15), 25-30, 2018
142018
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
142015
Getting started with particle Metropolis-Hastings for inference in nonlinear dynamical models
J Dahlin, TB Schön
arXiv preprint arXiv:1511.01707, 2015
132015
Hierarchical Bayesian ARX models for robust inference
J Dahlin, F Lindsten, TB Schön, A Wills
System Identification 16 (1), 131-136, 2012
122012
Accurate Gaussian mixture model smoothing using a two-filter approach
MP Balenzuela, J Dahlin, N Bartlett, AG Wills, C Renton, B Ninness
2018 IEEE Conference on Decision and Control (CDC), 694-699, 2018
112018
Quasi-Newton particle Metropolis-Hastings
J Dahlin, F Lindsten, TB Schön
IFAC-PapersOnLine 48 (28), 981-986, 2015
112015
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
112014
On robust input design for nonlinear dynamical models
PE Valenzuela, J Dahlin, CR Rojas, TB Schön
Automatica 77, 268-278, 2017
102017
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Artiklar 1–20