Volumetric emission tomography for combustion processes
This is a comprehensive, critical, and pedagogical review of volumetric emission
tomography for combustion processes. Many flames that are of interest to scientists and …
tomography for combustion processes. Many flames that are of interest to scientists and …
Survey of multifidelity methods in uncertainty propagation, inference, and optimization
B Peherstorfer, K Willcox, M Gunzburger - Siam Review, 2018 - SIAM
In many situations across computational science and engineering, multiple computational
models are available that describe a system of interest. These different models have varying …
models are available that describe a system of interest. These different models have varying …
Deep learning in photoacoustic tomography: current approaches and future directions
A Hauptmann, B Cox - Journal of Biomedical Optics, 2020 - spiedigitallibrary.org
Biomedical photoacoustic tomography, which can provide high-resolution 3D soft tissue
images based on optical absorption, has advanced to the stage at which translation from the …
images based on optical absorption, has advanced to the stage at which translation from the …
A survey of projection-based model reduction methods for parametric dynamical systems
Numerical simulation of large-scale dynamical systems plays a fundamental role in studying
a wide range of complex physical phenomena; however, the inherent large-scale nature of …
a wide range of complex physical phenomena; however, the inherent large-scale nature of …
Learned reconstruction methods with convergence guarantees: A survey of concepts and applications
In recent years, deep learning has achieved remarkable empirical success for image
reconstruction. This has catalyzed an ongoing quest for the precise characterization of the …
reconstruction. This has catalyzed an ongoing quest for the precise characterization of the …
A stochastic Newton MCMC method for large-scale statistical inverse problems with application to seismic inversion
We address the solution of large-scale statistical inverse problems in the framework of
Bayesian inference. The Markov chain Monte Carlo (MCMC) method is the most popular …
Bayesian inference. The Markov chain Monte Carlo (MCMC) method is the most popular …
Optical tomography: forward and inverse problems
SR Arridge, JC Schotland - Inverse problems, 2009 - iopscience.iop.org
This is a review of recent mathematical and computational advances in optical tomography.
We discuss the physical foundations of forward models for light propagation on microscopic …
We discuss the physical foundations of forward models for light propagation on microscopic …
[图书][B] Thermal radiation in disperse systems: an engineering approach
LA Dombrovsky, D Baillis - 2010 - academia.edu
A number of technological processes and natural phenomena are accompanied by heat
transfer concerned with media thermal radiation. Generally, thermal radiation is thought to …
transfer concerned with media thermal radiation. Generally, thermal radiation is thought to …
Parameter and state model reduction for large-scale statistical inverse problems
A greedy algorithm for the construction of a reduced model with reduction in both parameter
and state is developed for an efficient solution of statistical inverse problems governed by …
and state is developed for an efficient solution of statistical inverse problems governed by …
Non‐linear model reduction for uncertainty quantification in large‐scale inverse problems
We present a model reduction approach to the solution of large‐scale statistical inverse
problems in a Bayesian inference setting. A key to the model reduction is an efficient …
problems in a Bayesian inference setting. A key to the model reduction is an efficient …