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Christian A. Naesseth
Christian A. Naesseth
Assistant Professor at University of Amsterdam
Verifierad e-postadress på uva.nl - Startsida
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Variational Sequential Monte Carlo
CA Naesseth, SW Linderman, R Ranganath, DM Blei
The 21st International Conference on Artificial Intelligence and Statistics …, 2018
2252018
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
1222017
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
1032015
Nested Sequential Monte Carlo Methods
CA Naesseth, F Lindsten, TB Schön
The 32nd International Conference on Machine Learning (ICML) 37, 1292–1301, 2015
892015
Elements of Sequential Monte Carlo
CA Naesseth, F Lindsten, TB Schön
Foundations and Trends® in Machine Learning 12 (3), 307-392, 2019
832019
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
522017
Sequential Monte Carlo for Graphical Models
CA Naesseth, F Lindsten, TB Schön
Advances in Neural Information Processing Systems 27, 2014
512014
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
402016
Markovian Score Climbing: Variational Inference with KL(p||q)
CA Naesseth, F Lindsten, D Blei
Advances in Neural Information Processing Systems 34, 2020
372020
High-dimensional filtering using nested sequential Monte Carlo
CA Naesseth, F Lindsten, TB Schön
IEEE Transactions on Signal Processing 67 (16), 4177-4188, 2019
262019
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
192018
Variational Combinatorial Sequential Monte Carlo Methods for Bayesian Phylogenetic Inference
AK Moretti, L Zhang, CA Naesseth, H Venner, D Blei, I Pe'er
The 37th Conference on Uncertainty in Artificial Intelligence (UAI), 2021
132021
A Variational Perspective on Generative Flow Networks
H Zimmermann, F Lindsten, JW van de Meent, CA Naesseth
Transactions on Machine Learning Research, 2023
62023
Capacity estimation of two-dimensional channels using Sequential Monte Carlo
CA Naesseth, F Lindsten, TB Schön
The 2014 IEEE Information Theory Workshop, 2014
62014
E-valuating classifier two-sample tests
T Pandeva, T Bakker, CA Naesseth, P Forré
arXiv preprint arXiv:2210.13027, 2022
52022
Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport
L Zhang, DM Blei, CA Naesseth
Transactions on Machine Learning Research, 2023
42023
Towards Automated Sequential Monte Carlo for Probabilistic Graphical Models
CA Naesseth, F Lindsten, TB Schön
NIPS Workshop on Black Box Inference and Learning, 2015
42015
Practical and asymptotically exact conditional sampling in diffusion models
L Wu, BL Trippe, CA Naesseth, DM Blei, JP Cunningham
arXiv preprint arXiv:2306.17775, 2023
22023
Machine learning using approximate inference: Variational and sequential Monte Carlo methods
CA Naesseth
Linköping University Electronic Press, 2018
22018
Importance sampling with Hamiltonian dynamics
CA Naesseth, F Lindsten
NIPS 2015 workshop for scalable Monte Carlo methods, 2015
22015
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Artiklar 1–20