31 citations · 46 across the 9 of their papers we have counts for
10 papers
Bayesian Inversion Beyond the Generator's Range: Reducing Non-physical Constraints from Generative Neural Networks
Pratyay Roy, Xuebin Zhao, Andrew Curtis
To address non-uniqueness in geophysical inversions, Generative Neural Networks (GNNs) are often used to parameterise geological or other prior information in a lower-dimensional s…
Designing Solutions to Geophysical Inverse Problems by Changing Variables
Xuebin Zhao, Andrew Curtis, Klaus Mosegaard
Geoscientists often solve inverse problems to estimate values of parameters of interest given relevant data sets. Bayesian inference solves these problems by combining probability…
Linearised versus Nonlinear Estimates of Uncertainty in Full Waveform Inversion
Xuebin Zhao, Andrew Curtis
Seismic full waveform inversion (FWI) is a powerful technique to generate high resolution images of the Earth's interior. However, significant uncertainty exists in all FWI solutio…
Variational and Monte Carlo Methods for Bayesian Inversion of Dynamic Subsurface Flow Simulations Using Seismic and Fluid Pressure Data
Zhen Zhang, Xuebin Zhao, Andrew Curtis
In order to predict future performance of subsurface fluid reservoirs under possible operating scenarios, a dynamic, porous-medium flow simulation model must be tuned to include re…
Detecting Model Misspecification in Bayesian Inverse Problems via Variational Gradient Descent
Qingyang Liu, Matthew A. Fisher, Zheyang Shen +4
Bayesian inference is optimal when the statistical model is well-specified, while outside this setting Bayesian inference can catastrophically fail; accordingly a wealth of post-Ba…
Direct-3D Variational Bayesian Surface Wave Inversion and Its Application to Ambient Noise Tomography beneath Great Britain
Xuebin Zhao, Lily Irvin, Erica Galetti +1
We present a new, variational, fully nonlinear, probabilistic ambient noise tomography method, which estimates subsurface structure and quantifies the corresponding uncertainties d…
Efficient Bayesian Full Waveform Inversion and Analysis of Prior Hypotheses in 3D
Xuebin Zhao, Andrew Curtis
Spatially 3-dimensional seismic full waveform inversion (3D FWI) is a highly nonlinear and computationally demanding inverse problem that constructs 3D subsurface seismic velocity…
Variational Prior Replacement in Bayesian Inference and Inversion
Xuebin Zhao, Andrew Curtis
Many scientific investigations require that the values of a set of model parameters are estimated using recorded data. In Bayesian inference, information from both observed data an…
Bayesian Inversion, Uncertainty Analysis and Interrogation using Boosting Variational Inference
Xuebin Zhao, Andrew Curtis
Geoscientists use observed data to estimate properties of the Earth's interior. This often requires non-linear inverse problems to be solved and uncertainties to be estimated. Baye…
An introduction to variational inference in Geophysical inverse problems
Xin Zhang, Muhammad Atif Nawaz, Xuebin Zhao +1
In a variety of scientific applications we wish to characterize a physical system using measurements or observations. This often requires us to solve an inverse problem, which usua…