Publications
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Recent pre-prints
- [J*]
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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]
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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]
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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]
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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]
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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]
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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]
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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]
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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]
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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]
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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]
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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]
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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
![Christian Andersson Naesseth](chran60.jpg)
PhD Student in Automatic Control
(Swedish: Doktorand i reglerteknik)
- Phone:
- +46 13 281087
- E-mail:
- christian.a.naesseth_at_liu.se
- Address:
- Dept. of Electrical Engineering
- Linköping University
- SE-581 83 Linköping
- Sweden
- Visiting Address:
- Campus Valla
- Building B
- Room 2A:522 (in the A corridor on the ground floor between entrance 25 and 27)
Informationsansvarig: Christian Andersson Naesseth
Senast uppdaterad: 2019-01-10