A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification

13 January 2020

Papers citing "A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification"

7 / 7 papers shown

Title
Learned multiphysics inversion with differentiable programming and machine learning M. Louboutin Ziyi Yin Rafael Orozco Thomas J. Grady Ali Siahkoohi G. Rizzuti Philipp A. Witte O. Møyner Gerard Gorman Felix J. Herrmann AI4CE 26 10 0 12 Apr 2023
Uncertainty Quantification for Deep Unrolling-Based Computational Imaging Canberk Ekmekci Müjdat Çetin UQCV 19 11 0 02 Jul 2022
Deep Bayesian inference for seismic imaging with tasks Ali Siahkoohi G. Rizzuti Felix J. Herrmann BDL UQCV 30 21 0 10 Oct 2021
Learning by example: fast reliability-aware seismic imaging with normalizing flows Ali Siahkoohi Felix J. Herrmann OOD 27 13 0 13 Apr 2021
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows Ali Siahkoohi G. Rizzuti Philipp A. Witte Felix J. Herrmann AI4CE 16 16 0 15 Jul 2020
Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach Ali Siahkoohi G. Rizzuti Felix J. Herrmann 25 20 0 01 Apr 2020
Stochastic seismic waveform inversion using generative adversarial networks as a geological prior L. Mosser O. Dubrule M. Blunt GAN AI4CE 89 206 0 10 Jun 2018