Numerical Generalized Randomized Hamiltonian Monte Carlo for piecewise smooth target densities
Fuente:
arXiv
Saved in:
| Main Authors: | Tran, Jimmy Huy, Kleppe, Tore Selland |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Tuning diagonal scale matrices for HMC
by: Tran, Jimmy Huy, et al.
Published: (2024)
by: Tran, Jimmy Huy, et al.
Published: (2024)
Randomized Runge-Kutta-Nyström Methods for Unadjusted Hamiltonian and Kinetic Langevin Monte Carlo
by: Bou-Rabee, Nawaf, et al.
Published: (2023)
by: Bou-Rabee, Nawaf, et al.
Published: (2023)
Numerical Generalized Randomized HMC processes for restricted domains
by: Kleppe, Tore Selland, et al.
Published: (2023)
by: Kleppe, Tore Selland, et al.
Published: (2023)
Log‐density gradient covariance and automatic metric tensors for Riemann manifold Monte Carlo methods
by: Tore Selland Kleppe
Published: (2024)
by: Tore Selland Kleppe
Published: (2024)
Incorporating Local Step-Size Adaptivity into the No-U-Turn Sampler using Gibbs Self Tuning
by: Bou-Rabee, Nawaf, et al.
Published: (2024)
by: Bou-Rabee, Nawaf, et al.
Published: (2024)
The Within-Orbit Adaptive Leapfrog No-U-Turn Sampler
by: Bou-Rabee, Nawaf, et al.
Published: (2025)
by: Bou-Rabee, Nawaf, et al.
Published: (2025)
Markov chain Monte Carlo without evaluating the target: an auxiliary variable approach
by: Yuan, Wei, et al.
Published: (2024)
by: Yuan, Wei, et al.
Published: (2024)
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC
by: Llorente, F., et al.
Published: (2021)
by: Llorente, F., et al.
Published: (2021)
Efficient Online Variational Estimation via Monte Carlo Sampling
by: Chagneux, Mathis, et al.
Published: (2026)
by: Chagneux, Mathis, et al.
Published: (2026)
Scalable Monte Carlo for Bayesian Learning
by: Fearnhead, Paul, et al.
Published: (2024)
by: Fearnhead, Paul, et al.
Published: (2024)
Stereographic Markov Chain Monte Carlo
by: Yang, Jun, et al.
Published: (2022)
by: Yang, Jun, et al.
Published: (2022)
Randomized Quasi-Monte Carlo Features for Kernel Approximation
by: Huang, Yian, et al.
Published: (2025)
by: Huang, Yian, et al.
Published: (2025)
Automated Efficient Estimation using Monte Carlo Efficient Influence Functions
by: Agrawal, Raj, et al.
Published: (2024)
by: Agrawal, Raj, et al.
Published: (2024)
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms
by: Lau, Tim Tsz-Kit, et al.
Published: (2023)
by: Lau, Tim Tsz-Kit, et al.
Published: (2023)
Parsimonious Gaussian mixture models with piecewise-constant eigenvalue profiles
by: Szwagier, Tom, et al.
Published: (2025)
by: Szwagier, Tom, et al.
Published: (2025)
MCMC using $\textit{bouncy}$ Hamiltonian dynamics: A unifying framework for Hamiltonian Monte Carlo and piecewise deterministic Markov process samplers
by: Chin, Andrew, et al.
Published: (2024)
by: Chin, Andrew, et al.
Published: (2024)
Monte Carlo inference for semiparametric Bayesian regression
by: Kowal, Daniel R., et al.
Published: (2023)
by: Kowal, Daniel R., et al.
Published: (2023)
Entropic Mirror Monte Carlo
by: Cherradi, Anas, et al.
Published: (2026)
by: Cherradi, Anas, et al.
Published: (2026)
Adaptive Meta-Learning Stochastic Gradient Hamiltonian Monte Carlo Simulation for Bayesian Updating of Structural Dynamic Models
by: Meng, Xianghao, et al.
Published: (2026)
by: Meng, Xianghao, et al.
Published: (2026)
Gaussian Invariant Markov Chain Monte Carlo
by: Titsias, Michalis K., et al.
Published: (2025)
by: Titsias, Michalis K., et al.
Published: (2025)
Monte Carlo and quasi-Monte Carlo integration for likelihood functions
by: Tang, Yanbo
Published: (2025)
by: Tang, Yanbo
Published: (2025)
Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy
by: You, Kisung
Published: (2026)
by: You, Kisung
Published: (2026)
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)
Robust Inference of Dynamic Covariance Using Wishart Processes and Sequential Monte Carlo
by: Huijsdens, Hester, et al.
Published: (2024)
by: Huijsdens, Hester, et al.
Published: (2024)
Bures-Wasserstein Importance-Weighted Evidence Lower Bound: Exposition and Applications
by: Jiang, Peiwen, et al.
Published: (2026)
by: Jiang, Peiwen, et al.
Published: (2026)
Inversion-Free Natural Gradient Descent on Riemannian Manifolds
by: Draca, Dario, et al.
Published: (2026)
by: Draca, Dario, et al.
Published: (2026)
Vertical Consensus Inference for High-Dimensional Random Partition
by: Nguyen, Khai, et al.
Published: (2026)
by: Nguyen, Khai, et al.
Published: (2026)
Accurate Large-sample Uncertainty Quantification using Stochastic Gradient Markov Chain Monte Carlo
by: Wang, Yu, et al.
Published: (2026)
by: Wang, Yu, et al.
Published: (2026)
Exact Bayesian Gaussian Cox Processes Using Random Integral
by: Tang, Bingjing, et al.
Published: (2024)
by: Tang, Bingjing, et al.
Published: (2024)
Bayesian penalized empirical likelihood and Markov Chain Monte Carlo sampling
by: Chang, Jinyuan, et al.
Published: (2024)
by: Chang, Jinyuan, et al.
Published: (2024)
Fast Rerandomization for Balancing Covariates in Randomized Experiments: A Metropolis-Hastings Framework
by: Lu, Jiuyao, et al.
Published: (2026)
by: Lu, Jiuyao, et al.
Published: (2026)
On Prediction Feature Assignment in the Heckman Selection Model
by: Mai, Huy, et al.
Published: (2023)
by: Mai, Huy, et al.
Published: (2023)
Adaptive tuning of Hamiltonian Monte Carlo methods
by: Akhmatskaya, Elena, et al.
Published: (2025)
by: Akhmatskaya, Elena, et al.
Published: (2025)
Two-sample comparison through additive tree models for density ratios
by: Awaya, Naoki, et al.
Published: (2025)
by: Awaya, Naoki, et al.
Published: (2025)
Expected information gain estimation via density approximations: Sample allocation and dimension reduction
by: Li, Fengyi, et al.
Published: (2024)
by: Li, Fengyi, et al.
Published: (2024)
Is Gibbs sampling faster than Hamiltonian Monte Carlo on GLMs?
by: Luu, Son, et al.
Published: (2024)
by: Luu, Son, et al.
Published: (2024)
Low-rank Bayesian matrix completion via geodesic Hamiltonian Monte Carlo on Stiefel manifolds
by: Cui, Tiangang, et al.
Published: (2024)
by: Cui, Tiangang, et al.
Published: (2024)
Numerically robust Gaussian state estimation with singular observation noise
by: Krämer, Nicholas, et al.
Published: (2025)
by: Krämer, Nicholas, et al.
Published: (2025)
Generalized Random Forests using Fixed-Point Trees
by: Fleischer, David, et al.
Published: (2023)
by: Fleischer, David, et al.
Published: (2023)
Scalable piecewise smoothing with BART
by: Yee, Ryan, et al.
Published: (2024)
by: Yee, Ryan, et al.
Published: (2024)
Similar Items
-
Tuning diagonal scale matrices for HMC
by: Tran, Jimmy Huy, et al.
Published: (2024) -
Randomized Runge-Kutta-Nyström Methods for Unadjusted Hamiltonian and Kinetic Langevin Monte Carlo
by: Bou-Rabee, Nawaf, et al.
Published: (2023) -
Numerical Generalized Randomized HMC processes for restricted domains
by: Kleppe, Tore Selland, et al.
Published: (2023) -
Log‐density gradient covariance and automatic metric tensors for Riemann manifold Monte Carlo methods
by: Tore Selland Kleppe
Published: (2024) -
Incorporating Local Step-Size Adaptivity into the No-U-Turn Sampler using Gibbs Self Tuning
by: Bou-Rabee, Nawaf, et al.
Published: (2024)