Bayesian Approach to Inverse Problems, 2008. ,
DOI : 10.1002/9780470611197
URL : https://hal.archives-ouvertes.fr/hal-00400668
Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images, IEEE Trans. Pattern Anal. Mach. Intell, vol.6, issue.6, pp.721-741, 1984. ,
Nonlinear image recovery with half-quadratic regularization, IEEE Transactions on Image Processing, vol.4, issue.7, pp.932-946, 1995. ,
DOI : 10.1109/83.392335
Unsupervised Bayesian Convex Deconvolution Based on a Field With an Explicit Partition Function, IEEE Transactions on Image Processing, vol.17, issue.1, pp.16-26, 2008. ,
DOI : 10.1109/TIP.2007.911819
URL : https://hal.archives-ouvertes.fr/hal-00879198
Efficient sparse Bayesian learning via Gibbs sampling, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.3634-3637, 2010. ,
DOI : 10.1109/ICASSP.2010.5495896
Blind Deconvolution of Sparse Pulse Sequences Under a Minimum Distance Constraint: A Partially Collapsed Gibbs Sampler Method, IEEE Transactions on Signal Processing, vol.60, issue.6, pp.2727-2743, 2012. ,
DOI : 10.1109/TSP.2012.2190066
Microwave imaging of piecewise constant objects in a 2D-TE configuration, International Journal of Applied Electromagnetics and Mechanics, vol.26, issue.6, pp.167-174, 2007. ,
Joint NDT Image Restoration and Segmentation Using Gauss–Markov–Potts Prior Models and Variational Bayesian Computation, IEEE Transactions on Image Processing, vol.19, issue.9, pp.2265-2277, 2010. ,
DOI : 10.1109/TIP.2010.2047902
Bayesian estimation of regularization and point spread function parameters for Wiener???Hunt deconvolution, Journal of the Optical Society of America A, vol.27, issue.7, pp.1593-1607, 2010. ,
DOI : 10.1364/JOSAA.27.001593
URL : https://hal.archives-ouvertes.fr/hal-00674508
Gaussian Process for Recommender Systems, Lecture Notes in Computer Science, Knowledge Science, Engineering and Management, vol.7091, pp.56-67, 2011. ,
DOI : 10.1007/978-3-642-25975-3_6
On the correlation structure of some two-dimensional stationary processes, Biometrika, vol.59, issue.1, pp.43-48, 1972. ,
DOI : 10.1093/biomet/59.1.43
Fast sampling of Gaussian Markov random fields, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.2, pp.325-338, 2001. ,
DOI : 10.1111/1467-9868.00288
Spatial Modeling With Spatially Varying Coefficient Processes, Journal of the American Statistical Association, vol.98, issue.462, pp.387-396, 2003. ,
DOI : 10.1198/016214503000170
Classification of textures using Gaussian Markov random fields, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.33, issue.4, pp.959-963, 1985. ,
DOI : 10.1109/TASSP.1985.1164641
Markov Random Fields: Theory and Application, 1992. ,
MCMC-Based Image Reconstruction with Uncertainty Quantification, SIAM Journal on Scientific Computing, vol.34, issue.3, pp.1316-1332, 2012. ,
DOI : 10.1137/11085760X
Efficient MCMCbased image deblurring with Neumann boundary conditions, Electronic Transactions on Numerical Analysis, vol.40, pp.476-488, 2013. ,
Gaussian Markov Random Fields: Theory and Applications, ser. Monographs on Statistics and Applied Probability, 2005. ,
DOI : 10.1201/9780203492024
Stochastic artificial retinas: algorithm, optoelectronic circuits, and implementation, Applied Optics, vol.40, issue.23, pp.3861-3876, 2001. ,
DOI : 10.1364/AO.40.003861
URL : https://hal.archives-ouvertes.fr/hal-00862122
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods, 2003. ,
DOI : 10.1007/978-3-642-55760-6
Gaussian sampling by local perturbations, Proc. Int. Conf. on Neural Information Processing Systems (NIPS), pp.1858-1866, 2010. ,
Super-resolution in map-making based on a physical instrument model and regularized inversion. Application to SPIRE/Herschel, Astron. Astrophys, vol.539, 2012. ,
URL : https://hal.archives-ouvertes.fr/hal-00674514
Rééchantillonnage gaussien en grande dimension pour lesprobì emes inverses, Actes 24 e coll. GRETSI, 2013. ,
A conjugate direction sampler for normal distributions with a few computed examples, 2008. ,
Sampling Gaussian Distributions in Krylov Spaces with Conjugate Gradients, SIAM Journal on Scientific Computing, vol.34, issue.3, pp.312-334, 2012. ,
DOI : 10.1137/110831404
Implementing random scan Gibbs samplers, Computational Statistics, vol.89, issue.1, pp.177-196, 2005. ,
DOI : 10.1007/BF02736129
Optimizing random scan Gibbs samplers, Journal of Multivariate Analysis, vol.97, issue.10, pp.2071-2100, 2006. ,
DOI : 10.1016/j.jmva.2006.05.008
Adaptive Gibbs samplers and related MCMC methods, The Annals of Applied Probability, vol.23, issue.1, pp.66-98, 2013. ,
DOI : 10.1214/11-AAP806
Sampling High-Dimensional Gaussian Distributions for General Linear Inverse Problems, IEEE Signal Processing Letters, vol.19, issue.5, pp.251-254, 2012. ,
DOI : 10.1109/LSP.2012.2189104
URL : https://hal.archives-ouvertes.fr/hal-00779449
Langevin-type models i: Diffusions with given stationary distributions, and their discretizations, Methodology And Computing In Applied Probability, vol.1, issue.3, pp.283-306, 1999. ,
DOI : 10.1023/A:1010086427957
Hybrid Monte Carlo, Physics Letters B, vol.195, issue.2, pp.216-222, 1987. ,
DOI : 10.1016/0370-2693(87)91197-X
MCMC Using Hamiltonian Dynamics ,
DOI : 10.1201/b10905-6
Langevin and hessian with fisher approximation stochastic sampling for parameter estimation of structured covariance, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.3964-3967, 2011. ,
DOI : 10.1109/ICASSP.2011.5947220
URL : https://hal.archives-ouvertes.fr/hal-00668308
Markov Chain Monte Carlo in practice, Boca Raton, 1996. ,
Harris recurrence of Metropolis-within-Gibbs and trans-dimensional Markov chains, 38] S. Meyn and R. Tweedie, Markov chains and stochastic stability, pp.2123-2139, 1993. ,
DOI : 10.1214/105051606000000510
Gradient scan Gibbs sampler: An efficient high-dimensional sampler application in inverse problems, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015. ,
DOI : 10.1109/ICASSP.2015.7178739
URL : https://hal.archives-ouvertes.fr/hal-01225866
Efficient Gaussian Sampling for Solving Large-Scale Inverse Problems Using MCMC, IEEE Transactions on Signal Processing, vol.63, issue.1, pp.70-80, 2015. ,
DOI : 10.1109/TSP.2014.2367457
URL : https://hal.archives-ouvertes.fr/hal-01059414
Super-resolution image reconstruction: a technical overview, IEEE Signal Proc. Mag, pp.21-36, 2003. ,
An Improved Observation Model for Super-Resolution Under Affine Motion, IEEE Transactions on Image Processing, vol.15, issue.11, pp.3325-3337, 2006. ,
DOI : 10.1109/TIP.2006.881996
On the geometric convergence of the Gibbs sampler, J. R. Statist. Soc. B, vol.56, issue.2, pp.377-384, 1994. ,
Updating Schemes, Correlation Structure, Blocking and Parameterization for the Gibbs Sampler, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.59, issue.2, pp.291-317, 1997. ,
DOI : 10.1111/1467-9868.00070
Stability of the Gibbs sampler for Bayesian hierarchical models, Ann. Statist, vol.36, issue.1, pp.95-117, 2008. ,
Geometric Ergodicity of Gibbs and Block Gibbs Samplers for a Hierarchical Random Effects Model, Journal of Multivariate Analysis, vol.67, issue.2, pp.414-430, 1998. ,
DOI : 10.1006/jmva.1998.1778
Geometric Ergodicity and Scanning Strategies for Two-Component Gibbs Samplers, Communications in Statistics - Theory and Methods, vol.57, issue.15, pp.3125-3145, 2015. ,
DOI : 10.1214/07-AAP486