Jimmy Olsson - RankMe

34 papers A* 6A 2Misc 2Journal 23Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Categorical Reparameterization with Denoising Diffusion models. CoRR Samson Gourevitch, Alain Durmus, Eric Moulines, Jimmy Olsson, Yazid Janati
2026	J	`jnl`	When Test-Time Guidance Is Enough: Fast Image and Video Editing with Diffusion Guidance. CoRR Ahmed Ghorbel, Badr Moufad, Navid Bagheri Shouraki, Alain Oliviero Durmus, Thomas Hirtz, Eric Moulines, Jimmy Olsson, Yazid Janati
2025	A*	`conf`	A Mixture-Based Framework for Guiding Diffusion Models. ICML Yazid Janati, Badr Moufad, Mehdi Abou El Qassime, Alain Oliviero Durmus, Eric Moulines, Jimmy Olsson
2025	J	`jnl`	A Mixture-Based Framework for Guiding Diffusion Models. CoRR Yazid Janati, Badr Moufad, Mehdi Abou El Qassime, Alain Durmus, Eric Moulines, Jimmy Olsson
2025	J	`jnl`	Briding Diffusion Posterior Sampling and Monte Carlo methods: a survey. CoRR Yazid Janati, Alain Durmus, Jimmy Olsson, Eric Moulines
2025	J	`jnl`	Conditional Diffusion Models with Classifier-Free Gibbs-like Guidance. CoRR Badr Moufad, Yazid Janati, Alain Durmus, Ahmed Ghorbel, Eric Moulines, Jimmy Olsson
2025	J	`jnl`	Controllable protein design through Feynman-Kac steering. CoRR Erik Hartman, Jonas Wallin, Johan Malmström, Jimmy Olsson
2025	J	`jnl`	Efficient Zero-Shot Inpainting with Decoupled Diffusion Guidance. CoRR Badr Moufad, Navid Bagheri Shouraki, Alain Oliviero Durmus, Thomas Hirtz, Eric Moulines, Jimmy Olsson, Yazid Janati
2025	A	`conf`	Recursive Learning of Asymptotic Variational Objectives. AISTATS Alessandro Mastrototaro, Mathias Müller, Jimmy Olsson
2025	A*	`conf`	Variational Diffusion Posterior Sampling with Midpoint Guidance. ICLR Badr Moufad, Yazid Janati, Lisa Bedin, Alain Oliviero Durmus, Randal Douc, Eric Moulines, Jimmy Olsson
2024	J	`jnl`	Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors. CoRR Yazid Janati El Idrissi, Alain Durmus, Eric Moulines, Jimmy Olsson
2024	A*	`conf`	Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors. NeurIPS Yazid Janati, Badr Moufad, Alain Durmus, Eric Moulines, Jimmy Olsson
2024	A*	`conf`	Online Variational Sequential Monte Carlo. ICML Alessandro Mastrototaro, Jimmy Olsson
2024	J	`jnl`	Recursive Learning of Asymptotic Variational Objectives. CoRR Alessandro Mastrototaro, Mathias Müller, Jimmy Olsson
2024	J	`jnl`	Variational Diffusion Posterior Sampling with Midpoint Guidance. CoRR Badr Moufad, Yazid Janati, Lisa Bedin, Alain Durmus, Randal Douc, Eric Moulines, Jimmy Olsson
2023	J	`jnl`	A similarity-based Bayesian mixture-of-experts model. Stat. Comput. Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson
2023	J	`jnl`	Adaptive online variance estimation in particle filters: the ALVar estimator. Stat. Comput. Alessandro Mastrototaro, Jimmy Olsson
2023	J	`jnl`	Backward Importance Sampling for Online Estimation of State Space Models. J. Comput. Graph. Stat. Alice Martin, Marie-Pierre Étienne, Pierre Gloaguen, Sylvain Le Corff, Jimmy Olsson
2023	J	`jnl`	Online Variational Sequential Monte Carlo. CoRR Alessandro Mastrototaro, Jimmy Olsson
2023	A*	`conf`	State and parameter learning with PARIS particle Gibbs. ICML Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, Eric Moulines, Jimmy Olsson
2022	A*	`conf`	BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. NeurIPS Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson
2022	J	`jnl`	BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. CoRR Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson
2022	J	`jnl`	Boost your favorite Markov Chain Monte Carlo sampler using Kac's theorem: the Kick-Kac teleportation algorithm. CoRR Randal Douc, Alain Durmus, Aurélien Enfroy, Jimmy Olsson
2022	J	`jnl`	Sequential sampling of junction trees for decomposable graphs. Stat. Comput. Jimmy Olsson, Tatjana Pavlenko, Felix L. Rios
2020	J	`jnl`	A similarity-based Bayesian mixture-of-experts model. CoRR Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson
2019	J	`jnl`	Particle-Based Adaptive-Lag Online Marginal Smoothing in General State-Space Models. IEEE Trans. Signal Process. Johan Alenlöv, Jimmy Olsson
2018	J	`jnl`	Sequential sampling of junction trees for decomposable graphs. CoRR Jimmy Olsson, Tetyana Pavlenko, Felix L. Rios
2016	Misc	`conf`	Efficient parameter inference in general hidden Markov models using the filter derivatives. ICASSP Jimmy Olsson, Johan Westerborn
2015	J	`jnl`	On the use of Markov chain Monte Carlo methods for the sampling of mixture models: a statistical perspective. Stat. Comput. Randal Douc, Florian Maire, Jimmy Olsson
2014	J	`jnl`	Adaptive sequential Monte Carlo by means of mixture of experts. Stat. Comput. Julien Cornebise, Eric Moulines, Jimmy Olsson
2014	Misc	`conf`	Efficient particle-based online smoothing in general hidden Markov models. ICASSP Johan Westerborn, Jimmy Olsson
2010	A	`conf`	Approximation of hidden Markov models by mixtures of experts with application to particle filtering. AISTATS Jimmy Olsson, Jonas Ströjby
2008	—	`conf`	Adaptive methods for sequential importance sampling with application to state space models. EUSIPCO Julien Cornebise, Eric Moulines, Jimmy Olsson
2008	J	`jnl`	Adaptive methods for sequential importance sampling with application to state space models. Stat. Comput. Julien Cornebise, Eric Moulines, Jimmy Olsson