Publications

Coupling optimal experimental design and optimal control

World Congress on Computational Mechanics

Rebekah Dale White, Bart G van Bloemen Waanders, John Davis Jakeman, Alen Alexanderian, Arvind Saibaba

Machine learning in the context of inverse, control, and experimental design problems

Machine learning and deep learning -- internal Sandia conference

Rebekah Dale White, Bart G van Bloemen Waanders, John Davis Jakeman

Using Ultrasonic Attenuation in Cortical Bone to Infer Distributions on Pore Size

Applied Mathematical Modelling

Rebekah Dale White, Alen Alexanderian, Yasamin Karbalaeisadegh, Kidist Bekele-Maxwell, Harvey Thomas Banks, Maryline Talmant, Quentin Grimal, Marie Muller

https://www.osti.gov/search/identifier:1872035

Bayesian risk-averse optimal experimental design with feedback

UT Austin working group

Rebekah Dale White, Bart G van Bloemen Waanders, Drew Philip Kouri, John Davis Jakeman, Alen Alexanderian

Exploring risk-averse design criteria for sequential optimal experimental design in a Bayesian setting

Siam Uq

Rebekah Dale White, Bart G van Bloemen Waanders, John Davis Jakeman, Alexanderian Alen, Drew Philip Kouri

An inverse problem to infer cortical porosity from ultrasound attenuation data

quantitative musculoskeletal imaging (QMSKI) conference

Rebekah Dale White, Alen Alexanderian, Maryline Talmant, Quentin Grimal, Marie Muller

Exploring risk-averse design criteria for sequential optimal experimental design in a Bayesian setting

Mechanistic Machine Learning and Digital Twins for Compuational Science, Engineering & Technology

Rebekah Dale White, John Davis Jakeman, Bart G van Bloemen Waanders, Drew Philip Kouri, Alex Alexanderian