Jimmy Olsson

According to our database, Jimmy Olsson authored at least 27 papers between 2008 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

When Test-Time Guidance Is Enough: Fast Image and Video Editing with Diffusion Guidance.

Ahmed Ghorbel, Badr Moufad, Navid Bagheri Shouraki, Alain Oliviero Durmus, Thomas Hirtz, Eric Moulines, Jimmy Olsson, Yazid Janati

CoRR, February, 2026

Categorical Reparameterization with Denoising Diffusion models.

Samson Gourevitch, Alain Durmus, Eric Moulines, Jimmy Olsson, Yazid Janati

CoRR, January, 2026

2025

Efficient Zero-Shot Inpainting with Decoupled Diffusion Guidance.

Badr Moufad, Navid Bagheri Shouraki, Alain Oliviero Durmus, Thomas Hirtz, Eric Moulines, Jimmy Olsson, Yazid Janati

CoRR, December, 2025

Controllable protein design through Feynman-Kac steering.

Erik Hartman, Jonas Wallin, Johan Malmström, Jimmy Olsson

CoRR, November, 2025

Briding Diffusion Posterior Sampling and Monte Carlo methods: a survey.

Yazid Janati, Alain Durmus, Jimmy Olsson, Eric Moulines

CoRR, October, 2025

Conditional Diffusion Models with Classifier-Free Gibbs-like Guidance.

Badr Moufad, Yazid Janati, Alain Durmus, Ahmed Ghorbel, Eric Moulines, Jimmy Olsson

CoRR, May, 2025

A Mixture-Based Framework for Guiding Diffusion Models.

Yazid Janati, Badr Moufad, Mehdi Abou El Qassime, Alain Oliviero Durmus, Eric Moulines, Jimmy Olsson

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Variational Diffusion Posterior Sampling with Midpoint Guidance.

Badr Moufad, Yazid Janati, Lisa Bedin, Alain Oliviero Durmus, Randal Douc, Eric Moulines, Jimmy Olsson

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Recursive Learning of Asymptotic Variational Objectives.

Alessandro Mastrototaro, Mathias Müller, Jimmy Olsson

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors.

Yazid Janati El Idrissi, Alain Durmus, Eric Moulines, Jimmy Olsson

CoRR, 2024

Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors.

Yazid Janati, Badr Moufad, Alain Durmus, Eric Moulines, Jimmy Olsson

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Online Variational Sequential Monte Carlo.

Alessandro Mastrototaro, Jimmy Olsson

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

A similarity-based Bayesian mixture-of-experts model.

Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson

Stat. Comput., August, 2023

Adaptive online variance estimation in particle filters: the ALVar estimator.

Alessandro Mastrototaro, Jimmy Olsson

Stat. Comput., August, 2023

Backward Importance Sampling for Online Estimation of State Space Models.

Alice Martin, Marie-Pierre Étienne, Pierre Gloaguen, Sylvain Le Corff, Jimmy Olsson

J. Comput. Graph. Stat., 2023

State and parameter learning with PARIS particle Gibbs.

Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, Eric Moulines, Jimmy Olsson

Proceedings of the International Conference on Machine Learning, 2023

2022

Sequential sampling of junction trees for decomposable graphs.

Jimmy Olsson, Tatjana Pavlenko, Felix L. Rios

Stat. Comput., 2022

Boost your favorite Markov Chain Monte Carlo sampler using Kac's theorem: the Kick-Kac teleportation algorithm.

Randal Douc, Alain Durmus, Aurélien Enfroy, Jimmy Olsson

CoRR, 2022

BR-SNIS: Bias Reduced Self-Normalized Importance Sampling.

Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2019

Particle-Based Adaptive-Lag Online Marginal Smoothing in General State-Space Models.

Johan Alenlöv, Jimmy Olsson

IEEE Trans. Signal Process., 2019

2018

Sequential sampling of junction trees for decomposable graphs.

Jimmy Olsson, Tetyana Pavlenko, Felix L. Rios

CoRR, 2018

2016

Efficient parameter inference in general hidden Markov models using the filter derivatives.

Jimmy Olsson, Johan Westerborn

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015

On the use of Markov chain Monte Carlo methods for the sampling of mixture models: a statistical perspective.

Randal Douc, Florian Maire, Jimmy Olsson

Stat. Comput., 2015

2014

Adaptive sequential Monte Carlo by means of mixture of experts.

Julien Cornebise, Eric Moulines, Jimmy Olsson

Stat. Comput., 2014

Efficient particle-based online smoothing in general hidden Markov models.

Johan Westerborn, Jimmy Olsson

Proceedings of the IEEE International Conference on Acoustics, 2014

2010

Approximation of hidden Markov models by mixtures of experts with application to particle filtering.

Jimmy Olsson, Jonas Ströjby

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

2008

Adaptive methods for sequential importance sampling with application to state space models.

Julien Cornebise, Eric Moulines, Jimmy Olsson

Proceedings of the 2008 16th European Signal Processing Conference, 2008