Publications

Recent pre-prints

[J*]

C. A. Naesseth, F. Lindsten, T. B. Schön, High-dimensional Filtering using Nested Sequential Monte Carlo. arXiv.org, arXiv:1612.09162, 2016.

Refereed papers

[W2]

D. Lawson, G. Tucker, C. A. Naesseth, C. J. Maddison, R. P. Adams, Y. W. Teh, Twisted Variational Sequential Monte Carlo. Bayesian Deep Learning (NeurIPS Workshop), Montreal, Canada, December 2018.

[C7]

C. A. Naesseth, S. W. Linderman, R. Ranganath, D. M. Blei, Variational Sequential Monte Carlo. Proceedings of the 21st International Conference on Artificial Intelligence and Statistics, Lanzarote, Spain, April 2018.

[C6]

C. A. Naesseth, F. J. R. Ruiz, S. Linderman, D. M. Blei, Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, Fort Lauderdale, USA, April 2017. (Best Paper Award)

[J1]

F. Lindsten, A. M. Johansen, C. A. Naesseth, B. Kirkpatrick, T. B. Schön, J. Aston and A. Bouchard-Côté, Divide-and-Conquer with Sequential Monte Carlo. Journal of Computational and Graphical Statistics. 2016.

[C5]

T. Rainforth*, C. A. Naesseth*, F. Lindsten, B. Paige, J-W. van de Meent, A. Doucet, F. Wood, Interacting Particle Markov Chain Monte Carlo. Proceedings of the 33rd International Conference on Machine Learning (ICML), New York, USA, June 2016. * equal contribution

[C4]

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 (SYSID), Beijing, China, October 2015.

[C3]

C. A. Naesseth, F. Lindsten and T. B. Schön, Nested Sequential Monte Carlo Methods. Proceedings of the 32nd International Conference on Machine Learning (ICML), Lille, France, July 2015.

[W1]

C. A. Naesseth, F. Lindsten and T. B. Schön, Towards Automated Sequential Monte Carlo for Probabilistic Graphical Models. Black Box Inference and Learning NIPS Workshop, Montreal, Canada, December 2015.

[C2]

C. A. Naesseth, F. Lindsten and T. B. Schön, Sequential Monte Carlo for Graphical Models. Advances in Neural Information Processing Systems (NIPS) 27, Montreal, Canada, December 2014.

[C1]

C. A. Naesseth, F. Lindsten and T. B. Schön, Capacity estimation of two-dimensional channels using Sequential Monte Carlo. Proceedings of the 2014 IEEE Information Theory Workshop (ITW), Hobart, Australia, November 2014.

Other papers

[O1]

S. Khoshfetrat Pakazad, C. A. Naesseth, F. Lindsten and A. Hansson, Distributed, scalable and gossip-free consensus optimization with application to data analysis. arXiv.org, arXiv:1705.02469 , 2017.

Theses

[T2]

C. A. Naesseth, Vision and Radar Sensor Fusion for Advanced Driver Assistance Systems. Master's thesis, LiTH-ISY-EX-13/4685, 2013.

[T1]

C. A. Naesseth, Nowcasting using Microblog Data. Bachelor's thesis, LiTH-ISY-EX-ET-12/0398, 2012.