Efficient Bayesian computation by proximal Markov chain Monte Carlo: when Langevin meets Moreau

22 December 2016

Papers citing "Efficient Bayesian computation by proximal Markov chain Monte Carlo: when Langevin meets Moreau"

40 / 40 papers shown

Title
Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Jeffrey Wen Rizwan Ahmad Philip Schniter 29 0 0 14 May 2025
Diffusion at Absolute Zero: Langevin Sampling Using Successive Moreau Envelopes [conference paper] Andreas Habring Alexander Falk Thomas Pock 60 0 0 03 Feb 2025
Non-geodesically-convex optimization in the Wasserstein space Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Petrus Mikkola Marcelo Hartmann Kai Puolamaki Arto Klami 71 2 0 08 Jan 2025
Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction Jeffrey Wen Rizwan Ahmad Philip Schniter 41 2 0 28 May 2024
Convergence rates of particle approximation of forward-backward splitting algorithm for granular medium equations Matej Benko Iwona Chlebicka Jorgen Endal B. Miasojedow 32 1 0 28 May 2024
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation Hongwei Tan Ziruo Cai Marcelo Pereyra Subhadip Mukherjee Junqi Tang Carola-Bibiane Schönlieb SSL 76 1 0 08 Apr 2024
Proximal Oracles for Optimization and Sampling Jiaming Liang Yongxin Chen 44 3 0 02 Apr 2024
Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of Multipliers Alexandros E. Tzikas Licio Romao Mert Pilanci Alessandro Abate Mykel J. Kochenderfer 34 0 0 29 Jan 2024
Accelerating Neural Field Training via Soft Mining Shakiba Kheradmand Daniel Rebain Gopal Sharma Hossam N. Isack Abhishek Kar Andrea Tagliasacchi Kwang Moo Yi 45 4 0 29 Nov 2023
Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models Marien Renaud Jiaming Liu Valentin De Bortoli Andrés Almansa Ulugbek S. Kamilov 48 5 0 05 Oct 2023
Moreau-Yoshida Variational Transport: A General Framework For Solving Regularized Distributional Optimization Problems Dai Hai Nguyen Tetsuya Sakurai 29 1 0 31 Jul 2023
Non-convex sampling for a mixture of locally smooth potentials D. Nguyen 33 0 0 31 Jan 2023
Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity -- the Strongly Convex Case Tim Johnston Iosif Lytras Sotirios Sabanis 38 8 0 19 Jan 2023
Stable Deep MRI Reconstruction using Generative Priors Martin Zach Florian Knoll Thomas Pock OOD MedIm DiffM 33 17 0 25 Oct 2022
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling Jason M. Altschuler Kunal Talwar 38 24 0 16 Oct 2022
Efficient Bayes Inference in Neural Networks through Adaptive Importance Sampling Yunshi Huang Émilie Chouzenoux Victor Elvira J. Pesquet BDL 34 5 0 03 Oct 2022
Nesterov smoothing for sampling without smoothness JiaoJiao Fan Bo Yuan Jiaming Liang Yongxin Chen 37 2 0 15 Aug 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition Lukang Sun Avetik G. Karagulyan Peter Richtárik 26 19 0 01 Jun 2022
Optimized Population Monte Carlo Victor Elvira Émilie Chouzenoux 34 23 0 14 Apr 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents Alessandro Barp Lancelot Da Costa G. Francca Karl J. Friston Mark Girolami Michael I. Jordan G. Pavliotis 38 25 0 20 Mar 2022
A Proximal Algorithm for Sampling Jiaming Liang Yongxin Chen 30 17 0 28 Feb 2022
On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent R. Laumont Valentin De Bortoli Andrés Almansa J. Delon Alain Durmus Marcelo Pereyra 25 25 0 16 Jan 2022
Unadjusted Langevin algorithm for sampling a mixture of weakly smooth potentials D. Nguyen 21 5 0 17 Dec 2021
A Proximal Algorithm for Sampling from Non-smooth Potentials Jiaming Liang Yongxin Chen 47 26 0 09 Oct 2021
Fast Scalable Image Restoration using Total Variation Priors and Expectation Propagation D. Yao S. Mclaughlin Y. Altmann 13 6 0 04 Oct 2021
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension Alain Durmus A. Eberle 30 19 0 02 Aug 2021
Sampling with Mirrored Stein Operators Jiaxin Shi Chang-rui Liu Lester W. Mackey 49 19 0 23 Jun 2021
A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1 Adil Salim Lukang Sun Peter Richtárik 26 20 0 06 Jun 2021
Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie R. Laumont Valentin De Bortoli Andrés Almansa J. Delon Alain Durmus Marcelo Pereyra 26 109 0 08 Mar 2021
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 18 33 0 06 Nov 2020
Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm Adil Salim Peter Richtárik 22 38 0 16 Jun 2020
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness Murat A. Erdogdu Rasa Hosseinzadeh 11 75 0 27 May 2020
Wasserstein Control of Mirror Langevin Monte Carlo Kelvin Shuangjian Zhang Gabriel Peyré M. Fadili Marcelo Pereyra 19 65 0 11 Feb 2020
Maximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach. Part I: Methodology and Experiments A. F. Vidal Valentin De Bortoli Marcelo Pereyra Alain Durmus 24 7 0 26 Nov 2019
Langevin Monte Carlo without smoothness Niladri S. Chatterji Jelena Diakonikolas Michael I. Jordan Peter L. Bartlett BDL 15 43 0 30 May 2019
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 24 37 0 23 May 2019
Asymptotically exact data augmentation: models, properties and algorithms Maxime Vono N. Dobigeon P. Chainais 32 27 0 15 Feb 2019
A Primer on PAC-Bayesian Learning Benjamin Guedj 15 221 0 16 Jan 2019
Split-and-augmented Gibbs sampler - Application to large-scale inference problems Maxime Vono N. Dobigeon P. Chainais 19 50 0 16 Apr 2018
Mirrored Langevin Dynamics Ya-Ping Hsieh Ali Kavis Paul Rolland V. Cevher 16 81 0 27 Feb 2018