Fredrik Lindsten
Title
Cited by
Cited by
Year
Particle Gibbs with Ancestor Sampling
F Lindsten, MI Jordan, TB Schön
Journal of Machine Learning Research 15, 2145-2184, 2014
2242014
Backward simulation methods for Monte Carlo statistical inference
F Lindsten, TB Schön
Foundations and Trends® in Machine Learning 6 (1), 1-143, 2013
1442013
Bayesian inference and learning in Gaussian process state-space models with particle MCMC
R Frigola, F Lindsten, TB Schön, CE Rasmussen
arXiv preprint arXiv:1306.2861, 2013
1062013
Clustering using sum-of-norms regularization: With application to particle filter output computation
F Lindsten, H Ohlsson, L Ljung
2011 IEEE Statistical Signal Processing Workshop (SSP), 201-204, 2011
682011
Nested sequential Monte Carlo methods
CA Naesseth, F Lindsten, TB Schön
32nd International Conference on Machine Learning (ICML), 2015
642015
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
622015
Just relax and come clustering!: A convexification of k-means clustering
F Lindsten, H Ohlsson, L Ljung
Linköping University Electronic Press, 2011
582011
Ancestor sampling for particle Gibbs
F Lindsten, MI Jordan, TB Schön
Advances in Neural Information Processing Systems 25, 2600-2608, 2012
562012
Recursive maximum likelihood identification of jump Markov nonlinear systems
E Özkan, F Lindsten, C Fritsche, F Gustafsson
IEEE Transactions on Signal Processing 63 (3), 754-765, 2014
532014
An efficient stochastic approximation EM algorithm using conditional particle filters
F Lindsten
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
532013
Bayesian semiparametric Wiener system identification
F Lindsten, TB Schön, MI Jordan
Automatica 49 (7), 2053-2063, 2013
522013
Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering
S Lacoste-Julien, F Lindsten, F Bach
18th International Conference on Artificial Intelligence and Statistics …, 2015
512015
Sequential Monte Carlo for graphical models
CA Naesseth, F Lindsten, TB Schön
arXiv preprint arXiv:1402.0330, 2014
472014
Uniform ergodicity of the Particle Gibbs sampler
F Lindsten, R Douc, E Moulines
Scandinavian Journal of Statistics 42 (3), 775-797, 2015
452015
Rao-Blackwellised particle methods for inference and identification
F Lindsten
Linköping University Electronic Press, 2011
452011
Particle Metropolis–Hastings using gradient and Hessian information
J Dahlin, F Lindsten, TB Schön
Statistics and computing 25 (1), 81-92, 2015
442015
Geo-referencing for UAV navigation using environmental classification
F Lindsten, J Callmer, H Ohlsson, D Törnqvist, TB Schön, F Gustafsson
2010 IEEE International Conference on Robotics and Automation, 1420-1425, 2010
432010
Coherent modulation of the sea-level annual cycle in the United States by Atlantic Rossby waves
FM Calafat, T Wahl, F Lindsten, J Williams, E Frajka-Williams
Nature communications 9 (1), 1-13, 2018
422018
On the use of backward simulation in the particle Gibbs sampler
F Lindsten, TB Schön
37th IEEE International Conference on Acoustics, Speech, and Signal …, 2012
372012
Evaluating model calibration in classification
J Vaicenavicius, D Widmann, C Andersson, F Lindsten, J Roll, T Schön
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
332019
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