Results 11 to 20 of about 846,274 (324)
Bayesian inversion with α-stable priors
Inverse Problems, 2023 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.
Jarkko Suuronen +3 more
semanticscholar +3 more sources
Bayesian Inversion of Stokes Profiles [PDF]
Astronomy & Astrophysics, 2007 [abridged] Inversion techniques are the most powerful methods to obtain information about the thermodynamical and magnetic properties of solar and stellar atmospheres. In the last years, we have witnessed the development of highly sophisticated inversion
A. Asensio Ramos +49 more
core +5 more sources
Bayesian inference for inverse problems [PDF]
AIP Conference Proceedings, 2001 Traditionally, the MaxEnt workshops start by a tutorial day. This paper summarizes my talk during 2001'th workshop at John Hopkins University. The main idea in this talk is to show how the Bayesian inference can naturally give us all the necessary tools ...
Mohammad-Djafari, Ali
core +5 more sources
Stein variational reduced basis Bayesian inversion [PDF]
SIAM Journal on Scientific Computing, 2020 We propose and analyze a Stein variational reduced basis method (SVRB) to solve large-scale PDE-constrained Bayesian inverse problems. To address the computational challenge of drawing numerous samples requiring expensive PDE solves from the posterior ...
Peng Chen, O. Ghattas
semanticscholar +4 more sources
Derivative-Free Bayesian Inversion Using Multiscale Dynamics [PDF]
SIAM Journal on Applied Dynamical Systems, 2021 Inverse problems are ubiquitous because they formalize the integration of data with mathematical models. In many scientific applications the forward model is expensive to evaluate, and adjoint computations are difficult to employ; in this setting ...
G. Pavliotis, A. Stuart, U. Vaes
semanticscholar +1 more source
The research on Bayesian inference for geophysical inversion
地球与行星物理论评, 2022 Based on statistical theory, the Bayesian inversion method adopts the posterior probability distribution to evaluate the model parameters under the constraints of prior information and observation data.
Xingda Jiang, Wei Zhang, Hui Yang
doaj +1 more source
Review of Bayesian finite-fault source model inversion
地球与行星物理论评, 2023 A finite-fault earthquake slip model can characterize the kinematics of rupture, which is essential for earthquake mechanism studies and seismic hazard assessments.
Guoguang Wei +3 more
doaj +1 more source
Archives of Computational Methods in Engineering, 2022 The complexity of many problems in computational mechanics calls for reliable programming codes and accurate simulation systems. Typically, simulation responses strongly depend on material and model parameters, where one distinguishes between backward ...
N. Noii +6 more
semanticscholar +1 more source
Fast Bayesian inversion for high dimensional inverse problems
Statistics and Computing, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
B. Kugler, F. Forbes, S. Douté
semanticscholar +5 more sources
, 2021 We consider linear, mildly ill-posed inverse problems in separable Hilbert spaces under Gaussian noise, whose covariance operator is not identity (i.e. it is not a white noise problem), and use the Bayesian approach to nd their regularised solution. Speci cally, our goal is to regularise the prior in such a way that the posterior distribution achieves
Juan Chiachío-Ruano +2 more
+6 more sources