Cover Image

q-Analogue of Hamiltonian Monte Carlo method

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Xiaomei, Deng, Zhiliang
Format:	Preprint
Published:	2025
Subjects:	Numerical Analysis Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Covariance estimation using h-statistics in Monte Carlo and multilevel Monte Carlo methods
by: Shivanand, Sharana Kumar
Published: (2023)

Integration of bounded monotone functions: Revisiting the nonsequential case, with a focus on unbiased Monte Carlo (randomized) methods
by: Basak, Subhasish, et al.
Published: (2022)

Accelerating Langevin Monte Carlo via Efficient Stochastic Runge--Kutta Methods beyond Log-Concavity
by: Yang, Bin, et al.
Published: (2026)

Algorithmic warm starts for Hamiltonian Monte Carlo
by: Zhang, Matthew S., et al.
Published: (2026)

A polynomial chaos approach for uncertainty quantification of Monte Carlo transport codes
by: Geraci, Gianluca, et al.
Published: (2024)

Computable error bounds for quasi-Monte Carlo using points with non-negative local discrepancy
by: Gnewuch, Michael, et al.
Published: (2023)

Quasi-Monte Carlo confidence intervals using quantiles of randomized nets
by: Pan, Zexin
Published: (2025)

Speeding up Monte Carlo Integration: Control Neighbors for Optimal Convergence
by: Leluc, Rémi, et al.
Published: (2023)

Convergence of Kinetic Langevin Monte Carlo on Lie groups
by: Kong, Lingkai, et al.
Published: (2024)

Mean-Square Convergence of a New Parameterized Leapfrog Scheme for Hamiltonian Systems Driven by Gaussian Process Potentials
by: Bhattacharya, Sourabh
Published: (2026)

Uncertainty calibration for probabilistic projection methods
by: Fanaskov, Vladimir
Published: (2024)

Regularisation for the approximation of functions by mollified discretisation methods
by: Pouchol, Camille, et al.
Published: (2024)

Error analysis for a statistical finite element method
by: Karvonen, Toni, et al.
Published: (2022)

A Fourier-based inference method for learning interaction kernels in particle systems
by: Pavliotis, Grigorios A., et al.
Published: (2025)

Tensor-train methods for sequential state and parameter learning in state-space models
by: Zhao, Yiran, et al.
Published: (2023)

Reproducing kernel methods for machine learning, PDEs, and statistics
by: LeFloch, Philippe G., et al.
Published: (2024)

A Survey of Quantum Alternatives to Randomized Algorithms: Monte Carlo Integration and Beyond
by: Intallura, Philip, et al.
Published: (2023)

Stochastic Simulation and Monte Carlo Method
by: Mirzaei, Davoud
Published: (2025)

A kernel method for the learning of Wasserstein geometric flows
by: Hu, Jianyu, et al.
Published: (2025)

Hybrid Weight Window Techniques for Time-Dependent Monte Carlo Neutronics
by: Shaw, Caleb S., et al.
Published: (2025)

Persistent-Homology-Guided Topology Scanning of Qualitative Indicators for Acoustic Inverse Scattering
by: Yang, Xiaomei, et al.
Published: (2026)

A Closed-Form Transition Density Expansion for Elliptic and Hypo-Elliptic SDEs
by: Iguchi, Yuga, et al.
Published: (2025)

A global Lipschitz stability perspective for understanding approximate approaches in Bayesian sequential learning
by: Wang, Liliang, et al.
Published: (2025)

Blind free deconvolution over one-parameter sparse families via eigenmatrix
by: Ying, Lexing
Published: (2025)

Coverage errors for Student's t confidence intervals comparable to those in Hall (1988)
by: Owen, Art B.
Published: (2025)

Sparse free deconvolution under unknown noise level via eigenmatrix
by: Ying, Lexing
Published: (2025)

Stochastic Trace and Diagonal Estimator for Tensors
by: Verma, Bhisham Dev, et al.
Published: (2025)

A novel statistical workflow for nonstationary modelling of successive Fréchet extremes
by: Burtenshaw, Grace, et al.
Published: (2025)

A generalization bound for exit wave reconstruction via deep unfolding
by: Atwi, Moussa, et al.
Published: (2025)

Boosted optimal weighted least-squares
by: Haberstich, Cécile, et al.
Published: (2019)

Strong consistency of an estimator by the truncated singular value decomposition for an errors-in-variables regression model with collinearity
by: Aishima, Kensuke
Published: (2023)

One-dimensional Tensor Network Recovery
by: Chen, Ziang, et al.
Published: (2022)

On the contraction rate of the posterior distribution for nonlinear PDE parameter identification
by: Fan, Yuxin, et al.
Published: (2026)

Multi-fidelity No-U-Turn Sampling
by: Ravi, Kislaya, et al.
Published: (2023)

An Approximation Theory Framework for Measure-Transport Sampling Algorithms
by: Baptista, Ricardo, et al.
Published: (2023)

Extrapolation and generative algorithms for three applications in finance
by: LeFloch, Philippe G., et al.
Published: (2024)

Covariance-Informed Subspace: an Adaptive Gradient-Free Input Dimension Reduction Method for Bayesian Inference
by: Polette, Nadège, et al.
Published: (2026)

Central Limit Theorems for Coupled Particle Filters
by: Jasra, Ajay, et al.
Published: (2018)

Asymptotic analysis of the Gaussian kernel matrix for partially noisy data in high dimensions
by: Aishima, Kensuke
Published: (2026)

Extreme learning machines for variance-based global sensitivity analysis
by: Darges, John, et al.
Published: (2022)