Uncertainty Quantification in Deer Spectroscopy using Bayesian Statistical Inversion Methods

Bayesian Uncertainty Quantification for Subsurface Inversion Using a Multiscale Hierarchical Model

Bayesian Uncertainty Quantification for Subsurface Inversion Using a Multiscale Hierarchical Model Anirban Mondal, Bani Mallick, Yalchin Efendiev & Akhil Datta-Gupta a Department of Statistics, Texas A&M University, College Station, TX 77843 (; ) b Department of Mathematics, Texas A&M University, College Station, TX 77843 () c Petroleum Engineering Department, Texas A&M University, College Stat...

A Bayesian approach to quantifying uncertainty from experimental noise in DEER spectroscopy.

Double Electron-Electron Resonance (DEER) spectroscopy is a solid-state pulse Electron Paramagnetic Resonance (EPR) experiment that measures distances between unpaired electrons, most commonly between protein-bound spin labels separated by 1.5-8nm. From the experimental data, a distance distribution P(r) is extracted using Tikhonov regularization. The disadvantage of this method is that it does...

Uncertainty Quantification in Bayesian In- version

Probabilistic thinking is of growing importance in many areas of mathematics. This paper highlights the beautiful mathematical framework, coupled with practical algorithms, which results from thinking probabilistically about inverse problems arising in partial differential equations. Many inverse problems in the physical sciences require the determination of an unknown field from a finite set o...

A Gentle Tutorial on Statistical Inversion using the Bayesian Paradigm

Quantification of Uncertainty in Flow Simulations Using Probabilistic Methods