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We present Wideband Back-Projection Diffusion, an end-to-end probabilistic framework for approximating the posterior distribution induced by the inverse scattering map from wideband scattering data.
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Inverse problems= quest for information
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Yu Chen · 1997
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Inverse acoustic and electromagnetic scattering theory
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Seismic waveform inversion in the frequency domain; part 1: Theory and verification in a physical scale model
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A mathematical tutorial on synthetic aperture radar
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New stability estimates for the inverse acoustic inhomogeneous medium problem and applications
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The linear sampling method in inverse electromagnetic scattering theory
David Colton, Houssem Haddar, and Michele Piana · 2003
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Qualitative methods in inverse scattering theory: An introduction
Fioralba Cakoni and David Colton · 2005
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Inverse problem theory and methods for model parameter estimation
Albert Tarantola · 2005
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A review of the adjoint-state method for computing the gradient of a functional with geophysical applications
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Strictly proper scoring rules, prediction, and estimation
Tilmann Gneiting and Adrian E Raftery · 2007
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An overview of full-waveform inversion in exploration geophysics
J. Virieux and S. Operto · 2009
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The Analysis of Linear Partial Differential Operators. IV: Fourier Integral Operators
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Seismic tomography: A window into deep Earth
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Inverse problems: A bayesian perspective
A. M. Stuart · 2010
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An adaptive phase space method with application to reflection traveltime tomography
Eric Chung, Jianliang Qian, Gunther Uhlmann, and Hongkai Zhao · 2011
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Tweedie’s formula and selection bias
Bradley Efron · 2011
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A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
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Sweeping preconditioner for the Helmholtz equation: moving perfectly matched layers
B. Engquist and L. Ying · 2011
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Resolution analysis in full waveform inversion
Andreas Fichtner and Jeannot Trampert · 2011
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Probability and Statistics
Morris H. DeGroot and Mark J. Schervish · 2012
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Mitigating local minima in full-waveform inversion by expanding the search space
T. van Leeuwen and F. J. Herrmann · 2013
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Integral Equation Methods in Scattering Theory
D. Colton and R. Kress · 2013
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Integral Equation Methods in Scattering Theory
D. Colton and R. Kress · 2013
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Inverse Acoustic and Electromagnetic Scattering Theory
D. Colton and R. Kress · 2013
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Sinkhorn distances: Lightspeed computation of optimal transport
Marco Cuturi · 2013
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Auto-encoding variational Bayes
Diederik P. Kingma and Max Welling · 2014
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Improved detection of rough defects for ultrasonic nondestructive evaluation inspections based on finite element modeling of elastic wave scattering
J. R. Pettit, A. E. Walker, and M. J. S. Lowe · 2015
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Butterfly factorization
Yingzhou Li, Haizhao Yang, Eileen R. Martin, Kenneth L. Ho, and Lexing Ying · 2015
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Diederik P. Kingma and Jimmy Ba · 2015
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Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
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Invertible generative models for inverse problems: mitigating representation error and dataset bias
Muhammad Asim, Max Daniels, Oscar Leong, Ali Ahmed, and Paul Hand · 2020
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Jay Whang, Qi Lei, and Alex Dimakis · 2020
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Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Vincent Sitzmann, Julien N.P. Martel, David B. Lindell, and Gordon Wetzstein · 2020
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Unsupervised representation learning with deep convolutional generative adversarial networks
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Optimal transport for applied mathematicians
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The method of polarized traces for the 2D Helmholtz equation
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Fast alternating bidirectional preconditioner for the 2d high-frequency lippmann–schwinger equation
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Full-waveform inversion with extrapolated low-frequency data
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Improved denoising diffusion probabilistic models, 2021
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Deep equilibrium architectures for inverse problems in imaging
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Prior image-constrained reconstruction using style-based generative models
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A style-based generator architecture for generative adversarial networks
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Trumpets: Injective flows for inference and inverse problems
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Wide-band butterfly network: Stable and efficient inversion via multi-frequency neural networks
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Solving inverse wave scattering with deep learning
Yuwei Fan and Lexing Ying · 2022
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Implicit neural representation for mesh-free inverse obstacle scattering
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Denoising diffusion restoration models
Bahjat Kawar, Michael Elad, Stefano Ermon, and Jiaming Song · 2022
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Come-closer-diffuse-faster: Accelerating conditional diffusion models for inverse problems through stochastic contraction
Hyungjin Chung, Byeongsu Sim, and Jong Chul Ye · 2022
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Improving diffusion models for inverse problems using manifold constraints
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Elucidating the design space of diffusion-based generative models, 2022
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Optimal transport tools (ott): A JAX toolbox for all things Wasserstein
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Deep injective prior for inverse scattering
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User-defined event sampling and uncertainty quantification in diffusion models for physical dynamical systems
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High-frequency limit of the inverse scattering problem: Asymptotic convergence from inverse helmholtz to inverse liouville
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A neural network warm-start approach for the inverse acoustic obstacle scattering problem
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Debias coarsely, sample conditionally: Statistical downscaling through optimal transport and probabilistic diffusion models
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