Christian A. Naesseth
Christian A. Naesseth
Postdoctoral Research Scientist at Columbia University
Verified email at columbia.edu
Title
Cited by
Cited by
Year
Variational Sequential Monte Carlo
CA Naesseth, SW Linderman, R Ranganath, DM Blei
The 21st International Conference on Artificial Intelligence and Statistics …, 2018
1202018
Reparameterization gradients through acceptance-rejection sampling algorithms
CA Naesseth, FJR Ruiz, SW Linderman, DM Blei
The 20th International Conference on Artificial Intelligence and Statistics …, 2017
792017
Sequential Monte Carlo Methods for System Identification
TB Schön, F Lindsten, J Dahlin, J Wågberg, CA Naesseth, A Svensson, ...
IFAC Symposium on System Identification, 2015
672015
Nested Sequential Monte Carlo Methods
CA Naesseth, F Lindsten, TB Schön
The 32nd International Conference on Machine Learning (ICML) 37, 1292–1301, 2015
662015
Sequential Monte Carlo for Graphical Models
CA Naesseth, F Lindsten, TB Schön
Advances in Neural Information Processing Systems 27, 2014
462014
Divide-and-conquer with sequential Monte Carlo
F Lindsten, AM Johansen, CA Naesseth, B Kirkpatrick, TB Schön, ...
Journal of Computational and Graphical Statistics 26 (2), 445-458, 2017
282017
Interacting Particle Markov Chain Monte Carlo
T Rainforth, CA Naesseth, F Lindsten, B Paige, JW van de Meent, ...
The 33rd International Conference on Machine Learning (ICML) 48, 2616–2625, 2016
282016
Elements of Sequential Monte Carlo
CA Naesseth, F Lindsten, TB Schön
Foundations and Trends® in Machine Learning 12 (3), 307-392, 2019
222019
High-dimensional filtering using nested sequential Monte Carlo
CA Naesseth, F Lindsten, TB Schön
IEEE Transactions on Signal Processing 67 (16), 4177-4188, 2019
112019
Twisted Variational Sequential Monte Carlo
D Lawson, G Tucker, CA Naesseth, CJ Maddison, RP Adams, YW Teh
3rd workshop on Bayesian Deep Learning (NeurIPS), 2018
92018
Capacity estimation of two-dimensional channels using Sequential Monte Carlo
CA Naesseth, F Lindsten, TB Schön
The 2014 IEEE Information Theory Workshop, 2014
62014
Markovian Score Climbing: Variational Inference with KL(p||q)
CA Naesseth, F Lindsten, D Blei
Advances in Neural Information Processing Systems 34, 2020
52020
Towards Automated Sequential Monte Carlo for Probabilistic Graphical Models
CA Naesseth, F Lindsten, TB Schön
NIPS Workshop on Black Box Inference and Learning, 2015
52015
Importance sampling with Hamiltonian dynamics
CA Naesseth, F Lindsten
NIPS 2015 workshop for scalable Monte Carlo methods, 2015
22015
Machine learning using approximate inference: Variational and sequential Monte Carlo methods
CA Naesseth
Linköping University Electronic Press, 2018
12018
Distributed, scalable and gossip-free consensus optimization with application to data analysis
SK Pakazad, CA Naesseth, F Lindsten, A Hansson
arXiv preprint arXiv:1705.02469, 2017
12017
Robust Gaussian process regression with G-confluent likelihood
M Lindfors, T Chen, CA Naesseth
IFAC-PapersOnLine 53 (2), 394-399, 2020
2020
Inverse articulated-body dynamics from video via variational sequential Monte Carlo
D Biderman, CA Naesseth, L Wu, T Abe, AC Mosberger, LJ Sibener, ...
First workshop on differentiable vision, graphics, and physics applied to …, 2020
2020
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