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Jimmy Olsson
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2020 – today
- 2024
- [i6]Yazid Janati El Idrissi, Alain Durmus, Eric Moulines, Jimmy Olsson:
Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors. CoRR abs/2403.11407 (2024) - 2023
- [j8]Alice Martin, Marie-Pierre Étienne, Pierre Gloaguen, Sylvain Le Corff
, Jimmy Olsson
:
Backward Importance Sampling for Online Estimation of State Space Models. J. Comput. Graph. Stat. 32(4): 1447-1460 (2023) - [j7]Alessandro Mastrototaro
, Jimmy Olsson
:
Adaptive online variance estimation in particle filters: the ALVar estimator. Stat. Comput. 33(4): 77 (2023) - [j6]Tianfang Zhang
, Rasmus Bokrantz, Jimmy Olsson:
A similarity-based Bayesian mixture-of-experts model. Stat. Comput. 33(4): 83 (2023) - [c6]Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff
, Eric Moulines, Jimmy Olsson:
State and parameter learning with PARIS particle Gibbs. ICML 2023: 3625-3675 - [i5]Alessandro Mastrototaro, Jimmy Olsson:
Online Variational Sequential Monte Carlo. CoRR abs/2312.12616 (2023) - 2022
- [j5]Jimmy Olsson, Tatjana Pavlenko, Felix L. Rios
:
Sequential sampling of junction trees for decomposable graphs. Stat. Comput. 32(5): 80 (2022) - [c5]Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson:
BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. NeurIPS 2022 - [i4]Randal Douc, Alain Durmus, Aurélien Enfroy, Jimmy Olsson:
Boost your favorite Markov Chain Monte Carlo sampler using Kac's theorem: the Kick-Kac teleportation algorithm. CoRR abs/2201.05002 (2022) - [i3]Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson:
BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. CoRR abs/2207.06364 (2022) - 2020
- [i2]Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson:
A similarity-based Bayesian mixture-of-experts model. CoRR abs/2012.02130 (2020)
2010 – 2019
- 2019
- [j4]Johan Alenlöv
, Jimmy Olsson:
Particle-Based Adaptive-Lag Online Marginal Smoothing in General State-Space Models. IEEE Trans. Signal Process. 67(21): 5571-5582 (2019) - 2018
- [i1]Jimmy Olsson, Tetyana Pavlenko, Felix L. Rios:
Sequential sampling of junction trees for decomposable graphs. CoRR abs/1806.00584 (2018) - 2016
- [c4]Jimmy Olsson, Johan Westerborn
:
Efficient parameter inference in general hidden Markov models using the filter derivatives. ICASSP 2016: 3984-3988 - 2015
- [j3]Randal Douc
, Florian Maire, Jimmy Olsson:
On the use of Markov chain Monte Carlo methods for the sampling of mixture models: a statistical perspective. Stat. Comput. 25(1): 95-110 (2015) - 2014
- [j2]Julien Cornebise, Eric Moulines, Jimmy Olsson:
Adaptive sequential Monte Carlo by means of mixture of experts. Stat. Comput. 24(3): 317-337 (2014) - [c3]Johan Westerborn
, Jimmy Olsson:
Efficient particle-based online smoothing in general hidden Markov models. ICASSP 2014: 8003-8007 - 2010
- [c2]Jimmy Olsson, Jonas Ströjby:
Approximation of hidden Markov models by mixtures of experts with application to particle filtering. AISTATS 2010: 573-580
2000 – 2009
- 2008
- [j1]Julien Cornebise, Eric Moulines, Jimmy Olsson:
Adaptive methods for sequential importance sampling with application to state space models. Stat. Comput. 18(4): 461-480 (2008) - [c1]Julien Cornebise, Eric Moulines, Jimmy Olsson:
Adaptive methods for sequential importance sampling with application to state space models. EUSIPCO 2008: 1-5
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