:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Zhou, Quan
Format:	Preprint
Published:	2025
Subjects:	Computation Probability Machine Learning 60J20, 65C05, 65C40, 68Q25
Online Access:	https://arxiv.org/abs/2511.00708
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC
by: Zhou, Quan
Published: (2025)

A sharp uniform-in-time error estimate for Stochastic Gradient Langevin Dynamics
by: Li, Lei, et al.
Published: (2022)

Efficient Learning for Entropy-Regularized Markov Decision Processes via Multilevel Monte Carlo
by: Meunier, Matthieu, et al.
Published: (2025)

Diffusive Scaling Limits of Forward Event-Chain Monte Carlo: Provably Efficient Exploration with Partial Refreshment
by: Shiba, Hirofumi, et al.
Published: (2026)

Randomized sequential importance sampling for estimating the number of perfect matchings in bipartite graphs
by: Diaconis, Persi, et al.
Published: (2019)

Piecewise deterministic sampling with splitting schemes
by: Bertazzi, Andrea, et al.
Published: (2023)

A multilevel Monte Carlo algorithm for SDEs driven by countably dimensional Wiener process and Poisson random measure
by: Sobieraj, Michał
Published: (2023)

Spectral Gap of Metropolis Algorithms for Non-smooth Distributions under Isoperimetry
by: Liu, Shuigen, et al.
Published: (2026)

Central Limit Theorem for ergodic averages of Markov chains \& the comparison of sampling algorithms for heavy-tailed distributions
by: Brešar, Miha, et al.
Published: (2025)

Deep Learning without Global Optimization by Random Fourier Neural Networks
by: Davis, Owen, et al.
Published: (2024)

Mixing time of the conditional backward sampling particle filter
by: Karjalainen, Joona, et al.
Published: (2023)

Deep neural networks can provably solve Bellman equations for Markov decision processes without the curse of dimensionality
by: Jentzen, Arnulf, et al.
Published: (2025)

A Theory of Non-Acyclic Generative Flow Networks
by: Brunswic, Leo Maxime, et al.
Published: (2023)

High-Precision Framework for Expected Hitting Times Analysis in the Dice-Sum Process
by: Krityakierne, Tipaluck, et al.
Published: (2026)

Convergence of kinetic Langevin samplers for non-convex potentials
by: Schuh, Katharina, et al.
Published: (2024)

Deterministic computation of quantiles in a Lipschitz framework
by: Gu, Yurun, et al.
Published: (2024)

A high-order recombination algorithm for weak approximation of stochastic differential equations
by: Ninomiya, Syoiti, et al.
Published: (2025)

On couplings for kinetic Langevin diffusions
by: Bou-Rabee, Nawaf, et al.
Published: (2026)

Reflection coupling for unadjusted generalized Hamiltonian Monte Carlo in the nonconvex stochastic gradient case
by: Chak, Martin, et al.
Published: (2023)

Model reduction for fully nonlinear stochastic systems
by: Redmann, Martin
Published: (2025)

Rapid convergence of tempering chains to multimodal Gibbs measures
by: Son, Seungjae
Published: (2026)

Convergence and non-asymptotic error analysis for kinetic Langevin samplers using the exact harmonic Langevin integrator
by: Schuh, Katharina
Published: (2026)

Convergence of Langevin AIS for multimodal distributions
by: Agarwal, Akshat, et al.
Published: (2026)

Preconditioned Langevin Dynamics with Score-Based Generative Models for Infinite-Dimensional Linear Bayesian Inverse Problems
by: Baldassari, Lorenzo, et al.
Published: (2025)

Numerical solution to the Neumann problem in a Lipschitz domain, based on random walks
by: Lupascu-Stamate, Oana, et al.
Published: (2024)

Simulation of elliptic and hypo-elliptic conditional diffusions
by: Bierkens, Joris, et al.
Published: (2018)

Time-complexity of sampling from a multimodal distribution using sequential Monte Carlo
by: Han, Ruiyu, et al.
Published: (2025)

Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling
by: Klatzer, Teresa, et al.
Published: (2023)

Accelerated Simulation Algorithms for Extreme First-Passage Problems with General Emission Profiles
by: Mfoumou, Emmanuel Akame, et al.
Published: (2026)

Dimension reduction for large-scale stochastic systems with non-zero initial states and controlled diffusion
by: Redmann, Martin
Published: (2024)

Consistency of Learned Sparse Grid Quadrature Rules using NeuralODEs
by: Gottschalk, Hanno, et al.
Published: (2025)

Sampling elements of a finite group: efficiency of the product replacement algorithm with an accumulator
by: Marcinkowski, Michał, et al.
Published: (2025)

High order weak approximation of Stochastic Differential Equations for bounded and measurable test functions
by: Rey, Clément
Published: (2024)

Rosenthal-type inequalities for linear statistics of Markov chains
by: Durmus, Alain, et al.
Published: (2023)

Finite Sample Bounds for Sequential Monte Carlo and Adaptive Path Selection Using the $L_2$ Norm
by: Marion, Joe, et al.
Published: (2018)

First-passage time for PDifMPs: an Exact simulation approach for time-varying thresholds
by: Desmettre, Sascha, et al.
Published: (2025)

Reversibility of elliptical slice sampling revisited
by: Hasenpflug, Mareike, et al.
Published: (2023)

A Proximal-Gradient Method for Solving Regularized Optimization Problems with General Constraints
by: Curtis, Frank E., et al.
Published: (2025)

A Proximal-Gradient Method for Constrained Optimization
by: Dai, Yutong, et al.
Published: (2024)

The random timestep Euler method and its continuous dynamics
by: Latz, Jonas
Published: (2024)