Image de couverture de livre

A geometric approach to informed MCMC sampling

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Roy, Vivekananda
Format:	Preprint
Publié:	2024
Sujets:	Methodology Computation 65C05, 60J05
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

The No-Underrun Sampler: A Locally-Adaptive, Gradient-Free MCMC Method
par: Bou-Rabee, Nawaf, et autres
Publié: (2025)

Convergence of hybrid slice sampling via spectral gap
par: Łatuszyński, Krzysztof, et autres
Publié: (2014)

Parallel computations for Metropolis Markov chains with Picard maps
par: Grazzi, Sebastiano, et autres
Publié: (2025)

Parallel Affine Transformation Tuning of Markov Chain Monte Carlo
par: Schär, Philip, et autres
Publié: (2024)

Weak Poincaré inequality comparisons for ideal and hybrid slice sampling
par: Power, Sam, et autres
Publié: (2024)

Zig-zag sampling for discrete structures and non-reversible phylogenetic MCMC
par: Koskela, Jere
Publié: (2020)

Importance is Important: Generalized Markov Chain Importance Sampling Methods
par: Li, Guanxun, et autres
Publié: (2023)

Parallel MCMC Algorithms: Theoretical Foundations, Algorithm Design, Case Studies
par: Glatt-Holtz, Nathan E., et autres
Publié: (2022)

Solving the Poisson equation using coupled Markov chains
par: Douc, Randal, et autres
Publié: (2022)

Optimal convergence rates of MCMC integration for functions with unbounded second moment
par: Hofstadler, Julian
Publié: (2024)

Randomized Runge-Kutta-Nyström Methods for Unadjusted Hamiltonian and Kinetic Langevin Monte Carlo
par: Bou-Rabee, Nawaf, et autres
Publié: (2023)

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

Solving Poisson's equation for Wasserstein contractive Markov chains
par: Hofstadler, Julian
Publié: (2026)

On couplings for kinetic Langevin diffusions
par: Bou-Rabee, Nawaf, et autres
Publié: (2026)

Perturbation theory for killed Markov processes and quasi-stationary distributions
par: Rudolf, Daniel, et autres
Publié: (2021)

Nonparametric learning of stochastic differential equations from sparse and noisy data
par: Ganguly, Arnab, et autres
Publié: (2025)

An invitation to adaptive Markov chain Monte Carlo convergence theory
par: Laitinen, Pietari, et autres
Publié: (2024)

Central Limit Theorem for ergodic averages of Markov chains \& the comparison of sampling algorithms for heavy-tailed distributions
par: Brešar, Miha, et autres
Publié: (2025)

Piecewise deterministic sampling with splitting schemes
par: Bertazzi, Andrea, et autres
Publié: (2023)

Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration
par: Bou-Rabee, Nawaf, et autres
Publié: (2022)

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

On theoretical guarantees and a blessing of dimensionality for nonconvex sampling
par: Chak, Martin
Publié: (2024)

Time-complexity of sampling from a multimodal distribution using sequential Monte Carlo
par: Han, Ruiyu, et autres
Publié: (2025)

Convergence of kinetic Langevin samplers for non-convex potentials
par: Schuh, Katharina, et autres
Publié: (2024)

Simulation of elliptic and hypo-elliptic conditional diffusions
par: Bierkens, Joris, et autres
Publié: (2018)

Reflection coupling for unadjusted generalized Hamiltonian Monte Carlo in the nonconvex stochastic gradient case
par: Chak, Martin, et autres
Publié: (2023)

Spectral Gap of Metropolis Algorithms for Non-smooth Distributions under Isoperimetry
par: Liu, Shuigen, et autres
Publié: (2026)

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

Mixing time of the conditional backward sampling particle filter
par: Karjalainen, Joona, et autres
Publié: (2023)

Convergence of a Sequential Monte Carlo algorithm towards multimodal distributions on Rd
par: Han, Ruiyu
Publié: (2025)

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

Unbiased likelihood estimation of Wright-Fisher diffusion processes
par: García-Pareja, Celia, et autres
Publié: (2023)

The scaling limit of planar maps with large faces
par: Curien, Nicolas, et autres
Publié: (2025)

Surrogate-Based Bayesian Inference: Uncertainty Quantification and Active Learning
par: Roberts, Andrew Gerard, et autres
Publié: (2026)

Diffusive Scaling Limits of Forward Event-Chain Monte Carlo: Provably Efficient Exploration with Partial Refreshment
par: Shiba, Hirofumi, et autres
Publié: (2026)

PCA-Guided Quantile Sampling: Preserving Data Structure in Large-Scale Subsampling
par: Hui-Mean, Foo, et autres
Publié: (2025)

Rebalancing Markov jump processes for non-reversible continuous-time sampling
par: Jansson, Erik, et autres
Publié: (2025)

Reversibility of elliptical slice sampling revisited
par: Hasenpflug, Mareike, et autres
Publié: (2023)

Finite Sample Bounds for Sequential Monte Carlo and Adaptive Path Selection Using the $L_2$ Norm
par: Marion, Joe, et autres
Publié: (2018)

Unbiased simulation of Asian options
par: Bouchard, Bruno, et autres
Publié: (2025)