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
782017
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 Methods for System Identification
TB Schön, F Lindsten, J Dahlin, J Wågberg, CA Naesseth, A Svensson, ...
IFAC Symposium on System Identification, 2015
642015
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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