High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm

5 May 2016

Papers citing "High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm"

50 / 70 papers shown

Title
Operator-Level Quantum Acceleration of Non-Logconcave Sampling Jiaqi Leng Zhiyan Ding Zherui Chen Lin Lin 62 0 0 08 May 2025
Mirror Mean-Field Langevin Dynamics Anming Gu Juno Kim 31 0 0 05 May 2025
Improving the evaluation of samplers on multi-modal targets Louis Grenioux Maxence Noble Marylou Gabrié 110 0 0 11 Apr 2025
Diffusion at Absolute Zero: Langevin Sampling Using Successive Moreau Envelopes [conference paper] Andreas Habring Alexander Falk T. Pock 55 0 0 03 Feb 2025
Random Reshuffling for Stochastic Gradient Langevin Dynamics Luke Shaw Peter A. Whalley 82 3 0 28 Jan 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 53 2 0 08 Jan 2025
Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics Omar Chehab Anna Korba Austin Stromme Adrien Vacher 35 2 0 13 Oct 2024
On high-dimensional classification by sparse generalized Bayesian logistic regression The Tien Mai 46 1 0 19 Mar 2024
Nearly $d$ -Linear Convergence Bounds for Diffusion Models via Stochastic Localization Joe Benton Valentin De Bortoli Arnaud Doucet George Deligiannidis DiffM 41 101 0 07 Aug 2023
Contraction Rate Estimates of Stochastic Gradient Kinetic Langevin Integrators B. Leimkuhler Daniel Paulin P. Whalley 23 5 0 14 Jun 2023
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning Shuxin Zheng Jiyan He Chang-Shu Liu Yu Shi Ziheng Lu ... Peiran Jin Chi Chen Frank Noé Haiguang Liu Tie-Yan Liu AI4CE 19 41 0 08 Jun 2023
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm? Yuansi Chen Khashayar Gatmiry 94 15 0 10 Apr 2023
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation Ö. Deniz Akyildiz F. R. Crucinio Mark Girolami Tim Johnston Sotirios Sabanis 25 10 0 23 Mar 2023
Non-asymptotic analysis of Langevin-type Monte Carlo algorithms Shogo H. Nakakita 19 0 0 22 Mar 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression Avetik G. Karagulyan Peter Richtárik FedML 26 6 0 08 Mar 2023
Contraction and Convergence Rates for Discretized Kinetic Langevin Dynamics B. Leimkuhler Daniel Paulin P. Whalley 32 16 0 21 Feb 2023
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler Sivakanth Gopi Y. Lee Daogao Liu Ruoqi Shen Kevin Tian 17 7 0 13 Feb 2023
Non-convex sampling for a mixture of locally smooth potentials D. Nguyen 33 0 0 31 Jan 2023
Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions Marelys Crespo Navas S. Gadat X. Gendre 24 0 0 08 Jan 2023
Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration Nawaf Bou-Rabee Milo Marsden 32 12 0 20 Nov 2022
Jump-Diffusion Langevin Dynamics for Multimodal Posterior Sampling Jacopo Guidolin Vyacheslav Kungurtsev Ondvrej Kuvzelka BDL 16 0 0 02 Nov 2022
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms Vincent Plassier Alain Durmus Eric Moulines FedML 14 6 0 31 Oct 2022
Gaussian-Bernoulli RBMs Without Tears Renjie Liao Simon Kornblith Mengye Ren David J. Fleet Geoffrey E. Hinton BDL OOD 8 12 0 19 Oct 2022
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling Jason M. Altschuler Kunal Talwar 27 24 0 16 Oct 2022
Fisher information lower bounds for sampling Sinho Chewi P. Gerber Holden Lee Chen Lu 46 15 0 05 Oct 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition Lukang Sun Avetik G. Karagulyan Peter Richtárik 21 19 0 01 Jun 2022
Optimized Population Monte Carlo Victor Elvira Émilie Chouzenoux 24 23 0 14 Apr 2022
Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte Carlo L. Riou-Durand Jure Vogrinc 18 14 0 26 Feb 2022
HMC and underdamped Langevin united in the unadjusted convex smooth case Nicolai Gouraud Pierre Le Bris Adrien Majka Pierre Monmarché 20 10 0 02 Feb 2022
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi-An Ma Zhao-quan Song Guang Lin FedML 27 16 0 09 Dec 2021
Bounding Wasserstein distance with couplings N. Biswas Lester W. Mackey 17 8 0 06 Dec 2021
Statistical Finite Elements via Langevin Dynamics Ömer Deniz Akyildiz Connor Duffin Sotirios Sabanis Mark Girolami 25 11 0 21 Oct 2021
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint Y. Freund Yi-An Ma Tong Zhang 37 16 0 05 Oct 2021
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension Alain Durmus A. Eberle 24 19 0 02 Aug 2021
Uniform minorization condition and convergence bounds for discretizations of kinetic Langevin dynamics Alain Durmus Aurélien Enfroy Eric Moulines G. Stoltz 22 17 0 30 Jul 2021
Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo Vyacheslav Kungurtsev Adam D. Cobb T. Javidi Brian Jalaian 51 4 0 15 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 32 1,109 0 07 Jul 2021
Schr{ö}dinger-F{ö}llmer Sampler: Sampling without Ergodicity Jian Huang Yuling Jiao Lican Kang Xu Liao Jin Liu Yanyan Liu 29 27 0 21 Jun 2021
On log-concave approximations of high-dimensional posterior measures and stability properties in non-linear inverse problems Jan Bohr Richard Nickl 8 17 0 17 May 2021
Discrete sticky couplings of functional autoregressive processes Alain Durmus A. Eberle Aurélien Enfroy Arnaud Guillin Pierre Monmarché 11 7 0 14 Apr 2021
Data-Free Likelihood-Informed Dimension Reduction of Bayesian Inverse Problems Tiangang Cui O. Zahm 20 22 0 26 Feb 2021
On the cost of Bayesian posterior mean strategy for log-concave models S. Gadat Fabien Panloup Clément Pellegrini 18 7 0 08 Oct 2020
Convergence of Langevin Monte Carlo in Chi-Squared and Renyi Divergence Murat A. Erdogdu Rasa Hosseinzadeh Matthew Shunshi Zhang 86 41 0 22 Jul 2020
Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms A. Lovas Iosif Lytras Miklós Rásonyi Sotirios Sabanis 15 25 0 25 Jun 2020
A Non-Asymptotic Analysis for Stein Variational Gradient Descent Anna Korba Adil Salim Michael Arbel Giulia Luise A. Gretton 13 76 0 17 Jun 2020
On the limitations of single-step drift and minorization in Markov chain convergence analysis Qian Qin J. Hobert 12 29 0 21 Mar 2020
Central limit theorems for Markov chains based on their convergence rates in Wasserstein distance Rui Jin Aixin Tan 23 6 0 21 Feb 2020
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization Ömer Deniz Akyildiz Sotirios Sabanis 35 17 0 13 Feb 2020
Wasserstein Control of Mirror Langevin Monte Carlo Kelvin Shuangjian Zhang Gabriel Peyré M. Fadili Marcelo Pereyra 16 65 0 11 Feb 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo Y. Lee Ruoqi Shen Kevin Tian 19 37 0 10 Feb 2020