Dimension-independent likelihood-informed MCMC (Q2374891)

scientific article

Language	Label	Description	Also known as
English	Dimension-independent likelihood-informed MCMC	scientific article

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instance of

scholarly article

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title

Dimension-independent likelihood-informed MCMC (English)

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Journal of Computational Physics

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publication date

5 December 2016

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full work available at URL

https://arxiv.org/abs/1411.3688

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zbMATH Keywords

Markov chain Monte Carlo

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likelihood-informed subspace

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infinite-dimensional inverse problems

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Langevin SDE

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conditioned diffusion

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MaRDI profile type

MaRDI publication profile

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cites work

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Exact and Computationally Efficient Likelihood-Based Estimation for Discretely Observed Diffusion Processes (with Discussion)

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Weak convergence and optimal scaling of random walk Metropolis algorithms

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Optimal scaling for various Metropolis-Hastings algorithms.

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Diffusion limits of the random walk Metropolis algorithm in high dimensions

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Optimal scaling and diffusion limits for the Langevin algorithm in high dimensions

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MCMC methods for functions: modifying old algorithms to make them faster

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A sequential particle filter method for static models

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Sequential Monte Carlo Samplers

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Particle Markov Chain Monte Carlo Methods

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Multilevel Monte Carlo Path Simulation

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Complexity analysis of accelerated MCMC methods for Bayesian inversion

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A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow

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A Stochastic Newton MCMC Method for Large-Scale Statistical Inverse Problems with Application to Seismic Inversion

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Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods

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Proposals which speed up function-space MCMC

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Likelihood-informed dimension reduction for nonlinear inverse problems

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MAP estimators and their consistency in Bayesian nonparametric inverse problems

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Equation of State Calculations by Fast Computing Machines

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Monte Carlo sampling methods using Markov chains and their applications

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A note on Metropolis-Hastings kernels for general state spaces

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Optimal Scaling of Discrete Approximations to Langevin Diffusions

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Spectral gaps for a Metropolis-Hastings algorithm in infinite dimensions

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Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations

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A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems Part I: The Linearized Case, with Application to Global Seismic Inversion

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An adaptive Metropolis algorithm

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An adaptive version for the Metropolis adjusted Langevin algorithm with a truncated drift

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Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions

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Randomized algorithms for the low-rank approximation of matrices

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Q4448872

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On the ergodicity properties of some adaptive MCMC algorithms

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Coupling and Ergodicity of Adaptive Markov Chain Monte Carlo Algorithms

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On the ergodicity of the adaptive Metropolis algorithm on unbounded domains

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Langevin diffusions and Metropolis-Hastings algorithms

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A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems, Part II: Stochastic Newton MCMC with Application to Ice Sheet Flow Inverse Problems

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Active Subspace Methods in Theory and Practice: Applications to Kriging Surfaces

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A stable manifold MCMC method for high dimensions

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Stochastic Equations in Infinite Dimensions

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Identifiers

zbMATH Open document ID

1349.65009

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DOI

10.1016/j.jcp.2015.10.008

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:2374891