research
∙
04/02/2023
Ideal Observer Computation by Use of Markov-Chain Monte Carlo with Generative Adversarial Networks
Medical imaging systems are often evaluated and optimized via objective,...
share
research
∙
02/13/2023
Technical Note: PDE-constrained Optimization Formulation for Tumor Growth Model Calibration
We discuss solution algorithms for calibrating a tumor growth model usin...
research
∙
09/24/2022
Bayesian Inference of Tissue Heterogeneity for Individualized Prediction of Glioma Growth
Reliably predicting the future spread of brain tumors using imaging data...
research
∙
06/21/2022
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning
Neural operators have gained significant attention recently due to their...
research
∙
02/10/2022
Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problems
Tomographic imaging is in general an ill-posed inverse problem. Typicall...
research
∙
12/01/2021
hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty
Bayesian inference provides a systematic framework for integration of da...
research
∙
07/22/2021
A Predictive Multiphase Model of Silica Aerogels for Building Envelope Insulations
This work develops a multiphase thermomechanical model of porous silica ...
research
∙
07/12/2021
Parallel Element-based Algebraic Multigrid for H(curl) and H(div) Problems Using the ParELAG Library
This paper presents the use of element-based algebraic multigrid (AMGe) ...
research
∙
04/28/2021
Consensus ADMM for Inverse Problems Governed by Multiple PDE Models
The Alternating Direction Method of Multipliers (ADMM) provides a natura...
research
∙
02/08/2021
Bayesian Poroelastic Aquifer Characterization from InSAR Surface Deformation Data Part II: Quantifying the Uncertainty
Uncertainty quantification of groundwater (GW) aquifer parameters is cri...
research
∙
12/20/2020
A Predictive Discrete-Continuum Multiscale Model of Plasticity With Quantified Uncertainty
Multiscale models of materials, consisting of upscaling discrete simulat...
research
∙
11/30/2020
Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs
Many-query problems, arising from uncertainty quantification, Bayesian i...
research
∙
07/28/2020
Multilevel Hierarchical Decomposition of Finite Element White Noise with Application to Multilevel Markov Chain Monte Carlo
In this work we develop a new hierarchical multilevel approach to genera...
research
∙
12/03/2019
Proximal Newton Methods for X-Ray Imaging with Non-Smooth Regularization
Non-smooth regularization is widely used in image reconstruction to elim...
research
∙
09/09/2019
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs; Part I: Deterministic Inversion and Linearized Bayesian Inference
We present an extensible software framework, hIPPYlib, for solution of l...
research
∙
05/07/2019
