research
∙
06/21/2023
Corrector Operator to Enhance Accuracy and Reliability of Neural Operator Surrogates of Nonlinear Variational Boundary-Value Problems
This work focuses on developing methods for approximating the solution o...
share
research
∙
06/08/2023
Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data and machine learning surrogate
Identifying parameters of computational models from experimental data, o...
research
∙
03/16/2023
A phase-field model for non-small cell lung cancer under the effects of immunotherapy
Formulating tumor models that predict growth under therapy is vital for ...
research
∙
10/06/2022
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems
We explore using neural operators, or neural network representations of ...
research
∙
08/02/2022
Optimal design of chemoepitaxial guideposts for directed self-assembly of block copolymer systems using an inexact-Newton algorithm
Directed self-assembly (DSA) of block-copolymers (BCPs) is one of the mo...
research
∙
06/24/2022
Mutual-Information Based Optimal Experimental Design for Hyperpolarized ^13C-Pyruvate MRI
A key parameter of interest recovered from hyperpolarized (HP) MRI measu...
research
∙
06/22/2022
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport
We consider the Bayesian calibration of models describing the phenomenon...
research
∙
05/30/2022
Goal-Oriented A-Posteriori Estimation of Model Error as an Aid to Parameter Estimation
In this work, a Bayesian model calibration framework is presented that u...
research
∙
01/14/2022
A 1D-0D-3D coupled model for simulating blood flow and transport processes in breast tissue
In this work, we present mixed dimensional models for simulating blood f...
research
∙
02/24/2021
Quantitative in vivo imaging to enable tumor forecasting and treatment optimization
Current clinical decision-making in oncology relies on averages of large...
research
∙
10/28/2020
A globally convergent modified Newton method for the direct minimization of the Ohta-Kawasaki energy with application to the directed self-assembly of diblock copolymers
We propose a fast and robust scheme for the direct minimization of the O...
research
∙
07/04/2019