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OCEANS 2019 MTS/IEEE SEATTLE, 2019
Covering the vast majority of our planet, the ocean is still largely unmapped and unexplored. Various imaging techniques researched and developed over the past decades, ranging from echo-sounders on ships to LIDAR systems in the air, have only ...
W. Ali +6 more
semanticscholar +1 more source
Covering the vast majority of our planet, the ocean is still largely unmapped and unexplored. Various imaging techniques researched and developed over the past decades, ranging from echo-sounders on ships to LIDAR systems in the air, have only ...
W. Ali +6 more
semanticscholar +1 more source
2015
This chapter provides a general introduction, at the high level, to the backward propagation of uncertainty/information in the solution of inverse problems, and specifically a Bayesian probabilistic perspective on such inverse problems. Under the umbrella of inverse problems, we consider parameter estimation and regression.
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This chapter provides a general introduction, at the high level, to the backward propagation of uncertainty/information in the solution of inverse problems, and specifically a Bayesian probabilistic perspective on such inverse problems. Under the umbrella of inverse problems, we consider parameter estimation and regression.
openaire +1 more source
Bayesian linearized AVO inversion
GEOPHYSICS, 2003A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P‐wave velocity, S‐wave velocity, and density. Distributions for other elastic parameters can also be assessed—for example, acoustic impedance, shear impedance, and P‐wave to S‐wave velocity ratio.
Arild Buland, Henning Omre
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Crustal Imaging With Bayesian Inversion of Teleseismic P Wave Coda Autocorrelation
Journal of Geophysical Research: Solid Earth, 2019The autocorrelation of the seismic transmission response of a layered medium (autocorrelogram), in the presence of a free surface, corresponds to the reflection response.
Mehdi Tork Qashqai +2 more
semanticscholar +1 more source
Inversion-based Latent Bayesian Optimization
Neural Information Processing SystemsLatent Bayesian optimization (LBO) approaches have successfully adopted Bayesian optimization over a continuous latent space by employing an encoder-decoder architecture to address the challenge of optimization in a high dimensional or discrete input ...
Jaewon Chu +3 more
semanticscholar +1 more source
2011
The posterior distribution in a nonparametric inverse problem is shown to contract to the true parameter at a rate that depends on the smoothness of the parameter, and the smoothness and scale of the prior. Correct combinations of these characteristics lead to the minimax rate.
Knapik, B.T. +2 more
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The posterior distribution in a nonparametric inverse problem is shown to contract to the true parameter at a rate that depends on the smoothness of the parameter, and the smoothness and scale of the prior. Correct combinations of these characteristics lead to the minimax rate.
Knapik, B.T. +2 more
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Bayesian inference for inverse problems – statistical inversion
e & i Elektrotechnik und Informationstechnik, 2007Unlike deterministic inversion methods, statistical approaches are capable of taking into account inherent measurement and model uncertainties into the inverse problem solution in a very simple and natural way. Statistical inversion theory reformulates inverse problems as problems of Bayesian statistical inference. In this framework, the solution to an
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Bayesian reaction optimization as a tool for chemical synthesis
Nature, 2021Benjamin J Shields +2 more
exaly