Accelerating Langevin Monte Carlo Sampling: A Large Deviations Analysis
Fuente:
arXiv
Saved in:
| Main Authors: | Yao, Nian, Ali, Pervez, Tao, Xihua, Zhu, Lingjiong |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
High-Order Langevin Monte Carlo Algorithms
by: Dang, Thanh, et al.
Published: (2025)
by: Dang, Thanh, et al.
Published: (2025)
Accelerating Constrained Sampling: A Large Deviations Approach
by: Wang, Yingli, et al.
Published: (2025)
by: Wang, Yingli, et al.
Published: (2025)
Regime-Switching Langevin Monte Carlo Algorithms
by: Wang, Xiaoyu, et al.
Published: (2025)
by: Wang, Xiaoyu, et al.
Published: (2025)
Decentralized Proximal Stochastic Gradient Langevin Dynamics
by: Islam, Mohammad Rafiqul, et al.
Published: (2026)
by: Islam, Mohammad Rafiqul, et al.
Published: (2026)
Non-Reversible Langevin Algorithms for Constrained Sampling
by: Du, Hengrong, et al.
Published: (2025)
by: Du, Hengrong, et al.
Published: (2025)
Anchored Langevin Algorithms
by: Gurbuzbalaban, Mert, et al.
Published: (2025)
by: Gurbuzbalaban, Mert, et al.
Published: (2025)
Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances
by: Gao, Xuefeng, et al.
Published: (2024)
by: Gao, Xuefeng, et al.
Published: (2024)
Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling
by: Gürbüzbalaban, Mert, et al.
Published: (2022)
by: Gürbüzbalaban, Mert, et al.
Published: (2022)
Sampling non-log-concave densities via Hessian-free high-resolution dynamics
by: Wang, Xiaoyu, et al.
Published: (2026)
by: Wang, Xiaoyu, et al.
Published: (2026)
Convergence of Kinetic Langevin Monte Carlo on Lie groups
by: Kong, Lingkai, et al.
Published: (2024)
by: Kong, Lingkai, et al.
Published: (2024)
Non-asymptotic Analysis of Diffusion Annealed Langevin Monte Carlo for Generative Modelling
by: Cordero-Encinar, Paula, et al.
Published: (2025)
by: Cordero-Encinar, Paula, et al.
Published: (2025)
A hierarchical entropy method for the delocalization of bias in high-dimensional Langevin Monte Carlo
by: Lacker, Daniel, et al.
Published: (2025)
by: Lacker, Daniel, et al.
Published: (2025)
Parallelized Midpoint Randomization for Langevin Monte Carlo
by: Yu, Lu, et al.
Published: (2024)
by: Yu, Lu, et al.
Published: (2024)
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient
by: Dalalyan, Arnak S., et al.
Published: (2017)
by: Dalalyan, Arnak S., et al.
Published: (2017)
Wasserstein Convergence Guarantees for a General Class of Score-Based Generative Models
by: Gao, Xuefeng, et al.
Published: (2023)
by: Gao, Xuefeng, et al.
Published: (2023)
Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures
by: Miranda, Charles, et al.
Published: (2023)
by: Miranda, Charles, et al.
Published: (2023)
Non-asymptotic estimates for accelerated high order Langevin Monte Carlo algorithms
by: Neufeld, Ariel, et al.
Published: (2024)
by: Neufeld, Ariel, et al.
Published: (2024)
Langevin Monte-Carlo Provably Learns Depth Two Neural Nets at Any Size and Data
by: Kumar, Dibyakanti, et al.
Published: (2025)
by: Kumar, Dibyakanti, et al.
Published: (2025)
Non-asymptotic analysis of Langevin-type Monte Carlo algorithms
by: Nakakita, Shogo
Published: (2023)
by: Nakakita, Shogo
Published: (2023)
Analysis of kinetic Langevin Monte Carlo under the stochastic exponential Euler discretization from underdamped all the way to overdamped
by: Kim, Kyurae, et al.
Published: (2025)
by: Kim, Kyurae, et al.
Published: (2025)
Reverse-BSDE Monte Carlo
by: Batista, Jairon H. N., et al.
Published: (2025)
by: Batista, Jairon H. N., et al.
Published: (2025)
Sampling conditioned diffusions via Pathspace Projected Monte Carlo
by: Grafke, Tobias
Published: (2025)
by: Grafke, Tobias
Published: (2025)
Accelerating Multilevel Markov Chain Monte Carlo Using Machine Learning Models
by: Reddy, Sohail, et al.
Published: (2024)
by: Reddy, Sohail, et al.
Published: (2024)
Efficient Sampling on Riemannian Manifolds via Langevin MCMC
by: Cheng, Xiang, et al.
Published: (2024)
by: Cheng, Xiang, et al.
Published: (2024)
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo
by: Zheng, Haoyang, et al.
Published: (2024)
by: Zheng, Haoyang, et al.
Published: (2024)
Sampling via Stochastic Interpolants by Langevin-based Velocity and Initialization Estimation in Flow ODEs
by: Duan, Chenguang, et al.
Published: (2026)
by: Duan, Chenguang, et al.
Published: (2026)
Subspace Langevin Monte Carlo
by: Maunu, Tyler, et al.
Published: (2024)
by: Maunu, Tyler, et al.
Published: (2024)
Diffusion annealed Langevin dynamics: a theoretical study
by: Cattiaux, Patrick, et al.
Published: (2025)
by: Cattiaux, Patrick, et al.
Published: (2025)
Sampling and estimation on manifolds using the Langevin diffusion
by: Bharath, Karthik, et al.
Published: (2023)
by: Bharath, Karthik, et al.
Published: (2023)
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
by: Yang, Shangda, et al.
Published: (2024)
by: Yang, Shangda, et al.
Published: (2024)
Some aspects of robustness in modern Markov Chain Monte Carlo
by: Power, Sam, et al.
Published: (2025)
by: Power, Sam, et al.
Published: (2025)
Error estimates between SGD with momentum and underdamped Langevin diffusion
by: Guillin, Arnaud, et al.
Published: (2024)
by: Guillin, Arnaud, et al.
Published: (2024)
Hamiltonian Monte Carlo with Asymmetrical Momentum Distributions
by: Ghosh, Soumyadip, et al.
Published: (2021)
by: Ghosh, Soumyadip, et al.
Published: (2021)
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation
by: Zhang, Rui, et al.
Published: (2023)
by: Zhang, Rui, et al.
Published: (2023)
Algorithms and Scientific Software for Quasi-Monte Carlo, Fast Gaussian Process Regression, and Scientific Machine Learning
by: Sorokin, Aleksei G.
Published: (2025)
by: Sorokin, Aleksei G.
Published: (2025)
Approximation of group explainers with coalition structure using Monte Carlo sampling on the product space of coalitions and features
by: Kotsiopoulos, Konstandinos, et al.
Published: (2023)
by: Kotsiopoulos, Konstandinos, et al.
Published: (2023)
Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise
by: Dang, Thanh, et al.
Published: (2025)
by: Dang, Thanh, et al.
Published: (2025)
DIGing--SGLD: Decentralized and Scalable Langevin Sampling over Time--Varying Networks
by: Bajwa, Waheed U., et al.
Published: (2025)
by: Bajwa, Waheed U., et al.
Published: (2025)
A Dynamical System View of Langevin-Based Non-Convex Sampling
by: Karimi, Mohammad Reza, et al.
Published: (2022)
by: Karimi, Mohammad Reza, et al.
Published: (2022)
Convergence of Unadjusted Langevin in High Dimensions: Delocalization of Bias
by: Chen, Yifan, et al.
Published: (2024)
by: Chen, Yifan, et al.
Published: (2024)
Similar Items
-
High-Order Langevin Monte Carlo Algorithms
by: Dang, Thanh, et al.
Published: (2025) -
Accelerating Constrained Sampling: A Large Deviations Approach
by: Wang, Yingli, et al.
Published: (2025) -
Regime-Switching Langevin Monte Carlo Algorithms
by: Wang, Xiaoyu, et al.
Published: (2025) -
Decentralized Proximal Stochastic Gradient Langevin Dynamics
by: Islam, Mohammad Rafiqul, et al.
Published: (2026) -
Non-Reversible Langevin Algorithms for Constrained Sampling
by: Du, Hengrong, et al.
Published: (2025)