Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo

10 February 2022

Krishnakumar Balasubramanian

Sinho Chewi

Murat A. Erdogdu

Adil Salim

Matthew Shunshi Zhang

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Papers citing "Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo"

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Title
Mixing Time of the Proximal Sampler in Relative Fisher Information via Strong Data Processing Inequality Andre Wibisono 128 1 0 01 Jul 2025
Noise Conditional Variational Score Distillation Xinyu Peng Ziyang Zheng Yaoming Wang Han Li Nuowen Kan Wenrui Dai Chenglin Li Junni Zou Hongkai Xiong DiffM 106 0 0 11 Jun 2025
Split Gibbs Discrete Diffusion Posterior Sampling Wenda Chu Zihui Wu Yifan Chen Yang Song Yisong Yue 84 2 0 03 Mar 2025
On the query complexity of sampling from non-log-concave distributions Yuchen He Chihao Zhang 114 1 0 10 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 134 2 0 08 Jan 2025
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion Ye He Kevin Rojas Molei Tao DiffM 122 11 0 27 Feb 2024
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation Aniket Das Dheeraj M. Nagaraj 99 8 0 27 May 2023
Learning Rate Free Sampling in Constrained Domains Louis Sharrock Lester W. Mackey Christopher Nemeth 78 2 0 24 May 2023
Subsampling Error in Stochastic Gradient Langevin Diffusions Kexin Jin Chenguang Liu J. Latz 70 0 0 23 May 2023
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space Michael Diao Krishnakumar Balasubramanian Sinho Chewi Adil Salim BDL 68 29 0 10 Apr 2023
Regularized Stein Variational Gradient Flow Ye He Krishnakumar Balasubramanian Bharath K. Sriperumbudur Jianfeng Lu OT 65 12 0 15 Nov 2022
Sampling with Mollified Interaction Energy Descent Lingxiao Li Qiang Liu Anna Korba Mikhail Yurochkin Justin Solomon 77 17 0 24 Oct 2022
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling Jason M. Altschuler Kunal Talwar 107 25 0 16 Oct 2022
Fisher information lower bounds for sampling Sinho Chewi P. Gerber Holden Lee Chen Lu 115 15 0 05 Oct 2022
How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences Mikolaj Kasprzak Ryan Giordano Tamara Broderick 70 0 0 29 Sep 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition Lukang Sun Avetik G. Karagulyan Peter Richtárik 90 19 0 01 Jun 2022
Constrained Langevin Algorithms with L-mixing External Random Variables Yu Zheng Andrew G. Lamperski 83 6 0 27 May 2022
Improved Convergence Rate of Stochastic Gradient Langevin Dynamics with Variance Reduction and its Application to Optimization Yuri Kinoshita Taiji Suzuki 87 17 0 30 Mar 2022
A Proximal Algorithm for Sampling Jiaming Liang Yongxin Chen 104 18 0 28 Feb 2022
A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1 Adil Salim Lukang Sun Peter Richtárik 74 20 0 06 Jun 2021
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization Ömer Deniz Akyildiz Sotirios Sabanis 99 17 0 13 Feb 2020