Results 21 to 30 of about 800 (115)
Inverse problems: A Bayesian perspective [PDF]
Acta Numerica, 2010 The subject of inverse problems in differential equations is of enormous practical importance, and has also generated substantial mathematical and computational innovation. Typically some form of regularization is required to ameliorate ill-posed behaviour.
openaire +2 more sources
Hierarchical Bayesian level set inversion [PDF]
Statistics and Computing, 2016 The level set approach has proven widely successful in the study of inverse problems for interfaces, since its systematic development in the 1990s. Recently it has been employed in the context of Bayesian inversion, allowing for the quantification of uncertainty within the reconstruction of interfaces. However the Bayesian approach is very sensitive to
Matthew M. Dunlop +2 more
openaire +6 more sources
Bayesian inversion with α-stable priors
Inverse Problems, 2023 Abstract We propose using Lévy α-stable distributions to construct priors for Bayesian inverse problems. The construction is based on Markov fields with stable-distributed increments. Special cases include the Cauchy and Gaussian distributions, with stability indices α = 1, and α = 2, respectively. Our target is to show that these priors
Jarkko Suuronen +3 more
openaire +2 more sources
Bayesian seismic multi-scale inversion in complex Laplace mixed domains
Petroleum Science, 2017 Seismic inversion performed in the time or frequency domain cannot always recover the long-wavelength background of subsurface parameters due to the lack of low-frequency seismic records.
Kun Li, Xing-Yao Yin, Zhao-Yun Zong
doaj +1 more source
Bayesian Inference for Inverse Problems [PDF]
AIP Conference Proceedings, 2002 Inverse problems arise everywhere we have indirect measurement. Regularization and Bayesian inference methods are two main approaches to handle inverse problems. Bayesian inference approach is more general and has much more tools for developing efficient methods for difficult problems.
openaire +2 more sources
On the Well-posedness of Bayesian Inverse Problems [PDF]
SIAM/ASA Journal on Uncertainty Quantification, 2020 30 pages, 7 ...
openaire +3 more sources
Journal of Marine Science and Engineering, 2019 The key to model-based Bayesian geoacoustic inversion is to solve the posterior probability distributions (PPDs) of parameters. In order to obtain PPDs more efficiently and accurately, the state-of-the-art Markov chain Monte Carlo (MCMC) method, multiple-
Bo Zou +5 more
doaj +1 more source
Bayesian Approach to Inverse Quantum Statistics [PDF]
Physical Review Letters, 2000 A nonparametric Bayesian approach is developed to determine quantum potentials from empirical data for quantum systems at finite temperature. The approach combines the likelihood model of quantum mechanics with a priori information over potentials implemented in form of stochastic processes.
Lemm, J. C., Uhlig, J., Weiguny, A.
openaire +3 more sources
Bayesian Rotation Inversion of KIC 11145123 [PDF]
The Astrophysical Journal, 2022 Abstract A scheme of Bayesian rotation inversion, which allows us to compute the probability of a model of a stellar rotational profile, is developed. The validation of the scheme with simple rotational profiles and the corresponding sets of artificially generated rotational shifts has been successfully carried out, and we can correctly ...
Yoshiki Hatta +3 more
openaire +2 more sources
Parallelized Adaptive Importance Sampling for Solving Inverse Problems
Frontiers in Earth Science, 2018 In the field of groundwater hydrology and more generally geophysics, solving inverse problems in a complex, geologically realistic, and discrete model space often requires the usage of Monte Carlo methods.
Christoph Jäggli +2 more
doaj +1 more source