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Bayesian Inversion for Geoacoustic Parameters in Shallow Sea [PDF]
Sensors, 2020 Geoacoustic parameter inversion is a crucial issue in underwater acoustic research for shallow sea environments and has increasingly become popular in the recent past.
Guangxue Zheng +5 more
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Two-dimensional Bayesian inversion of magnetotelluric data using trans-dimensional Gaussian processes. [PDF]
Geophys J Int, 2021 Bayesian inversion of electromagnetic data produces crucial uncertainty information on inferred subsurface resistivity. Due to their high computational cost, however, Bayesian inverse methods have largely been restricted to computationally expedient 1-D ...
Blatter D, Ray A, Key K.
europepmc +2 more sources
Disintegration and Bayesian Inversion via String Diagrams [PDF]
Mathematical Structures in Computer Science, 2019 The notions of disintegration and Bayesian inversion are fundamental in conditional probability theory. They produce channels, as conditional probabilities, from a joint state, or from an already given channel (in opposite direction). These notions exist
Cho, Kenta, Jacobs, Bart
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InvertypeR: Bayesian inversion genotyping with Strand-seq data [PDF]
BMC Genomics, 2021 Background Single cell Strand-seq is a unique tool for the discovery and phasing of genomic inversions. Conventional methods to discover inversions with Strand-seq data are blind to known inversion locations, limiting their statistical power for the ...
Vincent C. T. Hanlon +4 more
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Ultrafast current imaging by Bayesian inversion [PDF]
Nature Communications, 2018 Scanning probe microscopy is widely used to characterize material properties with atomic resolution, yet electronic property mapping is normally constrained by slow data acquisition. Somnath et al.
S. Somnath +10 more
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Automatic Tempered Posterior Distributions for Bayesian Inversion Problems [PDF]
Mathematics, 2021 We propose a novel adaptive importance sampling scheme for Bayesian inversion problems where the inference of the variables of interest and the power of the data noise are carried out using distinct (but interacting) methods.
Luca Martino +4 more
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Bayesian Inversion, Uncertainty Analysis and Interrogation Using Boosting Variational Inference [PDF]
Journal of Geophysical Research: Solid Earth, 2023 Geoscientists use observed data to estimate properties of the Earth's interior. This often requires non‐linear inverse problems to be solved and uncertainties to be estimated. Bayesian inference solves inverse problems under a probabilistic framework, in
Xuebin Zhao, A. Curtis
semanticscholar +1 more source
Bayesian inversion for unified ductile phase-field fracture [PDF]
Computational Mechanics, 2021 The prediction of crack initiation and propagation in ductile failure processes are challenging tasks for the design and fabrication of metallic materials and structures on a large scale.
N. Noii +6 more
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Horseshoe Priors for Edge-Preserving Linear Bayesian Inversion [PDF]
SIAM Journal on Scientific Computing, 2022 In many large-scale inverse problems, such as computed tomography and image deblurring, characterization of sharp edges in the solution is desired. Within the Bayesian approach to inverse problems, edge-preservation is often achieved using Markov random ...
Felipe Uribe, Yiqiu Dong, P. Hansen
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Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors [PDF]
IEEE Transactions on Computational Imaging, 2022 Most modern imaging systems incorporate a computational pipeline to infer the image of interest from acquired measurements. The Bayesian approach to solve such ill-posed inverse problems involves the characterization of the posterior distribution of the ...
Pakshal Bohra +3 more
semanticscholar +1 more source