Two Metropolis--Hastings Algorithms for Posterior Measures with Non-Gaussian Priors in Infinite Dimensions
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Publication:5237191
DOI10.1137/18M1183017WikidataQ127127993 ScholiaQ127127993MaRDI QIDQ5237191
Publication date: 17 October 2019
Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1804.07833
Parametric inference (62F99) Monte Carlo methods (65C05) Discrete-time Markov processes on general state spaces (60J05) Inverse problems for PDEs (35R30) Probability theory on linear topological spaces (60B11)
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Background Driving Distribution Functions and Series Representations for Log-Gamma Self-Decomposable Random Variables ⋮ Spectral gaps and error estimates for infinite-dimensional Metropolis-Hastings with non-Gaussian priors ⋮ Gradient-Based Markov Chain Monte Carlo for Bayesian Inference With Non-differentiable Priors ⋮ Non-reversible guided Metropolis kernel ⋮ Besov-Laplace priors in density estimation: optimal posterior contraction rates and adaptation ⋮ Unnamed Item
Uses Software
Cites Work
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- Besov priors for Bayesian inverse problems
- Self-decomposability and Lévy processes in free probability
- A note on Metropolis-Hastings kernels for general state spaces
- Geometric MCMC for infinite-dimensional inverse problems
- Statistical and computational inverse problems.
- Well-posed Bayesian inverse problems and heavy-tailed stable quasi-Banach space priors
- Discretization-invariant Bayesian inversion and Besov space priors
- On noncentral generalized Laplacianness of quadratic forms in normal variables
- Dimension-independent likelihood-informed MCMC
- Multivariate subordination, self-decomposability and stability
- A Note on the Innovation Distribution of a Gamma Distributed Autoregressive Process
- Fast Gibbs sampling for high-dimensional Bayesian inversion
- Inverse problems: A Bayesian perspective
- Gamma processes
- An integral representation for selfdecomposable banach space valued random variables
- Time-reversibility of linear stochastic processes
- Random mappings on infinite dimensional spaces
- Self-decomposable probability measures on Banach spaces
- Well-Posed Bayesian Inverse Problems with Infinitely Divisible and Heavy-Tailed Prior Measures
- Computational Methods for Inverse Problems
- Fast Markov chain Monte Carlo sampling for sparse Bayesian inference in high-dimensional inverse problems using L1-type priors
- Well-Posed Bayesian Inverse Problems: Priors with Exponential Tails
- Dirichlet–Laplace Priors for Optimal Shrinkage
- Bayesian Inverse Problems with $l_1$ Priors: A Randomize-Then-Optimize Approach
- Introduction to Bayesian Scientific Computing
- A function space HMC algorithm with second order Langevin diffusion limit
- MCMC methods for functions: modifying old algorithms to make them faster
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