Cost free hyper-parameter selection/averaging for Bayesian inverse problems with vanilla and Rao-blackwellized SMC samplers
DOI10.1007/s11222-023-10294-4zbMath1523.62041arXiv2212.12205OpenAlexW4387106775MaRDI QIDQ6063154
Adam M. Johansen, Alberto Sorrentino, Alessandro Viani
Publication date: 7 November 2023
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2212.12205
empirical BayesBayesian inverse problemssequential Monte Carlo samplersfully Bayesianhyper-parameter estimationRao-blackwellization
Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Monte Carlo methods (65C05)
Cites Work
- An adaptive sequential Monte Carlo method for approximate Bayesian computation
- Where Bayes tweaks Gauss: conditionally Gaussian priors for stable multi-dipole estimation
- Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Application to maximum marginal likelihood and empirical Bayesian estimation
- Negative association, ordering and convergence of resampling methods
- Sequential Monte Carlo samplers with independent Markov chain Monte Carlo proposals
- Dynamic filtering of static dipoles in magnetoencephalography
- Monte Carlo strategies in scientific computing.
- Inverse problems: A Bayesian perspective
- Sequential Monte Carlo samplers for semi-linear inverse problems and application to magnetoencephalography
- Sequential Monte Carlo Samplers
- A Metric for Performance Evaluation of Multi-Target Tracking Algorithms
- Efficient Sequential Monte-Carlo Samplers for Bayesian Inference
- Global Consensus Monte Carlo
- An Introduction to Sequential Monte Carlo
- Bayesian multi-dipole modelling of a single topography in MEG by adaptive sequential Monte Carlo samplers
- Waste-Free Sequential Monte Carlo
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: Cost free hyper-parameter selection/averaging for Bayesian inverse problems with vanilla and Rao-blackwellized SMC samplers