Random tree Besov priors -- towards fractal imaging

DOI10.3934/ipi.2022059OpenAlexW3135039438MaRDI QIDQ2697377

Eero Saksman, Matti Lassas, Hanne Kekkonen, Samuli Siltanen

Publication date: 18 April 2023

Published in: Inverse Problems and Imaging (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2103.00574

zbMATH Keywords

waveletsinverse problemfractalsBayesian inversionstatistical inversionBesov priorsdiscretisation invariance

Mathematics Subject Classification ID

Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) Probabilistic models, generic numerical methods in probability and statistics (65C20) Fractals (28A80) Statistical distribution theory (62Exx)

Related Items (2)

Laplace priors and spatial inhomogeneity in Bayesian inverse problems ⋮ Besov-Laplace priors in density estimation: optimal posterior contraction rates and adaptation

Cites Work

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• Besov priors for Bayesian inverse problems
• Parallel cartoons of fractal models of finance
• The inescapable need for fractal tools in finance
• Asymptotic equivalence for nonparametric regression with multivariate and random design
• Function spaces and wavelets on domains
• Pólya tree posterior distributions on densities
• Rates of contraction of posterior distributions based on \(p\)-exponential priors
• Spike and slab Pólya tree posterior densities: adaptive inference
• Nonparametric Bayesian inference for reversible multidimensional diffusions
• Discretization-invariant Bayesian inversion and Besov space priors
• On infinite-dimensional hierarchical probability models in statistical inverse problems
• Extreme at-the-money skew in a local volatility model
• Adaptive wavelet thresholding for image denoising and compression
• Inverse problems: A Bayesian perspective
• Fractal Physiology and Chaos in Medicine
• Random Recursive Constructions: Asymptotic Geometric and Topological Properties
• Hierarchical models in statistical inverse problems and the Mumford–Shah functional
• A Gaussian hypermodel to recover blocky objects
• Hypermodels in the Bayesian imaging framework
• Wavelet Thresholding via A Bayesian Approach
• Ideal spatial adaptation by wavelet shrinkage
• Nonlinear wavelet image processing: variational problems, compression, and noise removal through wavelet shrinkage
• An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
• Can one use total variation prior for edge-preserving Bayesian inversion?
• Linear inverse problems for generalised random variables
• Markov Chain Monte Carlo Methods for High Dimensional Inversion in Remote Sensing
• Global Uniqueness in the Impedance-Imaging Problem for Less Regular Conductivities
• Theory of Function Spaces IV
• A THRESHOLD MODEL FOR LOCAL VOLATILITY: EVIDENCE OF LEVERAGE AND MEAN REVERSION EFFECTS ON HISTORICAL DATA
• MAP estimators and their consistency in Bayesian nonparametric inverse problems
• Noise reduction by wavelet thresholding
• On Hausdorff dimension of random fractals

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