Fast Markov chain Monte Carlo sampling for sparse Bayesian inference in high-dimensional inverse problems using L1-type priors

Inverse Problems

Volumn 28, Issue 12, 2012, Pages

  Lucka, Felix ^a  

^a UNIVERSITY OF MÜNSTER   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN FRAMEWORKS; BAYESIAN INFERENCE; BAYESIAN INVERSION; GIBBS SAMPLERS; HIGH-DIMENSIONAL; INTRINSIC FEATURES; MARKOV CHAIN MONTE CARLO; MCMC SAMPLING; PRIOR DISTRIBUTION; REGULARIZATION THEORY; SAMPLING ALGORITHM; SAMPLING SCHEMES; SINGLE COMPONENTS; SPARSE PRIOR; VARIATIONAL REGULARIZATION;

DIFFERENTIAL EQUATIONS; INFERENCE ENGINES; INVERSE PROBLEMS; LEARNING ALGORITHMS; MONTE CARLO METHODS; PROBABILITY DISTRIBUTIONS; VARIATIONAL TECHNIQUES;

BAYESIAN NETWORKS;

EID: 84870416863     PISSN: 02665611     EISSN: 13616420     Source Type: Journal    
DOI: 10.1088/0266-5611/28/12/125012     Document Type: Article

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