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Christian A. Naesseth
Christian A. Naesseth
Assistant Professor, University of Amsterdam
Verifisert e-postadresse på uva.nl - Startside
Tittel
Sitert av
Sitert av
År
Variational Sequential Monte Carlo
CA Naesseth, SW Linderman, R Ranganath, DM Blei
The 21st International Conference on Artificial Intelligence and Statistics …, 2018
2672018
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
1352017
Elements of Sequential Monte Carlo
CA Naesseth, F Lindsten, TB Schön
Foundations and Trends® in Machine Learning 12 (3), 307-392, 2019
1192019
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
1092015
Nested Sequential Monte Carlo Methods
CA Naesseth, F Lindsten, TB Schön
The 32nd International Conference on Machine Learning (ICML) 37, 1292–1301, 2015
912015
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
722017
Practical and asymptotically exact conditional sampling in diffusion models
L Wu, B Trippe, CA Naesseth, D Blei, JP Cunningham
Advances in Neural Information Processing Systems 36, 2023
702023
Markovian Score Climbing: Variational Inference with KL(p||q)
CA Naesseth, F Lindsten, D Blei
Advances in Neural Information Processing Systems 34, 2020
632020
Sequential Monte Carlo for Graphical Models
CA Naesseth, F Lindsten, TB Schön
Advances in Neural Information Processing Systems 27, 2014
522014
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
432016
High-dimensional filtering using nested sequential Monte Carlo
CA Naesseth, F Lindsten, TB Schön
IEEE Transactions on Signal Processing 67 (16), 4177-4188, 2019
412019
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
252018
A Variational Perspective on Generative Flow Networks
H Zimmermann, F Lindsten, JW van de Meent, CA Naesseth
Transactions on Machine Learning Research, 2023
222023
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
222021
Variational Flow Matching for Graph Generation
F Eijkelboom, G Bartosh, CA Naesseth, M Welling, JW van de Meent
Advances in Neural Information Processing Systems 37, 2024
102024
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling
G Bartosh, D Vetrov, CA Naesseth
Advances in Neural Information Processing Systems 37, 2024
102024
E-valuating classifier two-sample tests
T Pandeva, T Bakker, CA Naesseth, P Forré
Transactions on Machine Learning Research, 2024
102024
Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport
L Zhang, DM Blei, CA Naesseth
Transactions on Machine Learning Research, 2023
92023
Capacity estimation of two-dimensional channels using Sequential Monte Carlo
CA Naesseth, F Lindsten, TB Schön
The 2014 IEEE Information Theory Workshop, 2014
62014
Equivariant Neural Diffusion for Molecule Generation
FRJ Cornet, G Bartosh, MN Schmidt, CA Naesseth
Advances in Neural Information Processing Systems 37, 2024
52024
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Artikler 1–20