arXiv (All)
open access
Smoothed Picard Hamiltonian Monte Carlo
We develop a new low-accuracy sampler, called \emph{smoothed Picard Hamiltonian Monte Carlo}, which combines Gaussian smoothing, Picard iteration, and higher-order discretization. For a log-concave target $π\propto \exp(-V)$ in dimension $d$ satisfying $0 \prec αI \preceq \nabla^2 V \preceq βI$, wit
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Exact Bayes Regret and Asymptotic Optimality in High-Dimensional Gaussian Bandits#1076374
- Poisson-Corrector Complexity Bounds for Moreau--Yosida Unadjusted Langevin Sampling#1070083
- Delayed Acceptance Slice Sampling#1035365
- Sharp Stationary Gaussian Approximation for Constant-Stepsize SGD#1144111
- Empirical Bayesian Image Restoration by Langevin Sampling with a Denoising Diffusion Implicit Prior#171575
Record · ID 974985
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive