Uncertainty quantification in imaging and automatic horizon tracking: a
Bayesian deep-prior based approach

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Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach

1 April 2020

Felix J. Herrmann

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Papers citing "Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach"

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Title
A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification Ali Siahkoohi G. Rizzuti Felix J. Herrmann UQCV BDL 60 22 0 13 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 544 42,591 0 03 Dec 2019
Deep-seismic-prior-based reconstruction of seismic data using convolutional neural networks Qun Liu Lihua Fu Meng Zhang 23 60 0 20 Nov 2019
Learned imaging with constraints and uncertainty quantification Felix J. Herrmann Ali Siahkoohi G. Rizzuti UQCV 68 23 0 13 Sep 2019
A Bayesian Perspective on the Deep Image Prior Zezhou Cheng Matheus Gadelha Subhransu Maji Daniel Sheldon BDL UQCV 64 137 0 16 Apr 2019
Multi-resolution neural networks for tracking seismic horizons from few training images Bas Peters J. Granek E. Haber 47 46 0 26 Dec 2018
Task adapted reconstruction for inverse problems J. Adler Sebastian Lunz Olivier Verdier Carola-Bibiane Schönlieb Ozan Oktem 61 43 0 27 Aug 2018
Stochastic seismic waveform inversion using generative adversarial networks as a geological prior L. Mosser O. Dubrule M. Blunt GAN AI4CE 111 208 0 10 Jun 2018
Deep Image Prior Dmitry Ulyanov Andrea Vedaldi Victor Lempitsky SupR 125 3,166 0 29 Nov 2017
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 91 327 0 23 Dec 2015