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Publication	Type	Year
Characterizing and Propagating Model Discrepancy in PDE-Constrained Optimization USACM Thematic Conference on Uncertainty Quantification for Machine Learning Integrated Physics Modeling Joseph Lee Hart, Bart G van Bloemen Waanders	Conference Poster – 2022 Conference Poster	2022
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	Conference Presentation – 2022 Conference Presentation	2022
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	Conference Presentation – 2022 Conference Presentation	2022
Lightning talk: thermal batteries ASCR RISE project meeting Bart G van Bloemen Waanders	Presentation (non-conference) – 2022 Presentation (non-conference)	2022
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	Presentation (non-conference) – 2022 Presentation (non-conference)	2022
Hyper-differential sensitivity analysis with respect to model discrepancy ASCR RISE Project Meeting Joseph Lee Hart, Bart G van Bloemen Waanders	Presentation (non-conference) – 2022 Presentation (non-conference)	2022
Hyper-differential sensitivity analysis with respect to model discrepancy ECCOMAS Congress Joseph Lee Hart, Bart G van Bloemen Waanders	Conference Presentation – 2022 Conference Presentation	2022
Reinforcement Learning for PDE Control Problems Siam Uq 2022 Nickolas Winovich, Bart G van Bloemen Waanders, Deepanshu Verma, Lars Ruthotto	Conference Presentation – 2022 Conference Presentation	2022
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	Conference Presentation – 2022 Conference Presentation	2022
Hyper-Differential Sensitivity Analysis of Inverse Problems Governed by PDEs Joint Mathematics Meetings 2022 Isaac Paul Sunseri, Joseph Lee Hart, Alen Alexanderian, Bart G van Bloemen Waanders	Conference Presentation – 2021 Conference Presentation	2021
Hyper-differential sensitivity analysis with respect to model discrepancy The 8th European Congress on Computational Methods in Applied Sciences and Engineering Joseph Lee Hart, Bart G van Bloemen Waanders	Abstract – 2021 Abstract	2021
Stochastic Deep Model Reference Adaptive Control EIEE CDC conference Bart G van Bloemen Waanders, Girish Joshi, Girish Chowdhary	Conference Paper – 2021 Conference Paper	2021
Hyper-differential sensitivity analysis for model form error Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology Joseph Lee Hart, Bart G van Bloemen Waanders	Conference Presentation – 2021 Conference Presentation	2021
Characterizing Approximation Methods for Digital Twins in Scientific Computing Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology Zachary Benjamin Morrow, Bart G van Bloemen Waanders, John Davis Jakeman	Conference Presentation – 2021 Conference Presentation	2021
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	Conference Presentation – 2021 Conference Presentation	2021
Goal-oriented data-driven reduced-order modeling guided by hyper-differential sensitivity analysis CSRI Virtual Poster Blitz Shane Alexander McQuarrie, Bart G van Bloemen Waanders	Display or Poster (non-conference) – 2021 Display or Poster (non-conference)	2021
Trajectory Planning for Aerospace Vehicles using Deep Reinforcement Learning SciTech Dheeraj Kapilavai, Subhrajit Roychowdhury, Yiwei Fu, Lei Yu, Bart G van Bloemen Waanders https://www.osti.gov/search/identifier:1871420	Conference Paper – 2021 Conference Paper	2021
Bedrock Inversion and Hyper Differential Sensitivity Analysis for the Shallow Ice Model Numerical Analysis in Data Science Transition Workshop William Mcneil Reese, Joseph Lee Hart, Bart G van Bloemen Waanders, Mauro Perergo, John Davis Jakeman, Arvind Saibaba	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
Parallel Solver Framework for Mixed-Integer PDE-Constrained Optimization Cynthia Ann Phillips, Michelle Althea Chatter, Jonathan Eckstein, Alper Erturk, Ihab Fathy El-Kady, Romain Gerbe, Drew Philip Kouri, William Loughlin, Charles M. Reinke, Rohith Rokkam, Massimo Ruzzene, Chris Sugino, Calvin Swanson, Bart G van Bloemen Waanders https://www.osti.gov/search/identifier:1771009	SAND Report – 2021 SAND Report	2021
A Fast Solver for the Fractional Helmholtz Equation SIAM Journal on Scientific Computing Christian Alexander Glusa, Christian Alexander Glusa, Marta D'Elia, Harbir Antil, Chester J Weiss, Bart G van Bloemen Waanders https://www.osti.gov/search/identifier:1765762	Journal Article – 2021 Journal Article	2021
Hyper-Differential Sensitivity Analysis: Managing High Dimensional Uncertainty in Large-Scale Optimization Problems Uncertainty Management and Machine Learning in Engineering Applications Bart G van Bloemen Waanders, Joseph Lee Hart https://www.osti.gov/search/identifier:1877814	Conference Presentation – 2020 Conference Presentation	2020
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection SIAM Journal on Mathematics of Data Science Elizabeth Newman, Lars Ruthotto, Joseph Lee Hart, Bart G van Bloemen Waanders https://www.osti.gov/search/identifier:1834344	Journal Article – 2020 Journal Article	2020
Hyper-differential sensitivity analysis of PDE-constrained inverse problems AWM Math Research Competition 2020 Isaac Paul Sunseri, Bart G van Bloemen Waanders, Joseph Lee Hart, Alen Alexandarian https://www.osti.gov/search/identifier:1767902	Presentation (non-conference) – 2020 Presentation (non-conference)	2020
Peridynamics to Predict Fracturing in the Subsurface American Geophysical Union Fall Meeting Bart G van Bloemen Waanders, David John Littlewood, Daniel Z. Turner, Michael L. Parks https://www.osti.gov/search/identifier:1767099	Conference Paper – 2020 Conference Paper	2020
Efficient Training of Neural Network Surrogate Methods with Variable Projection Mathematical and Scientific Machine Learning Elizabeth - x Newman, Lar - x Ruthotto, Joseph Lee Hart, Bart G van Bloemen Waanders, Bart G van Bloemen Waanders https://www.osti.gov/search/identifier:1767098	Conference Paper – 2020 Conference Paper	2020
Document Title	Type	Year

Results 1–25 of 196

Publications

Characterizing and Propagating Model Discrepancy in PDE-Constrained Optimization

Coupling optimal experimental design and optimal control

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

Lightning talk: thermal batteries

Bayesian risk-averse optimal experimental design with feedback

Hyper-differential sensitivity analysis with respect to model discrepancy

Hyper-differential sensitivity analysis with respect to model discrepancy

Reinforcement Learning for PDE Control Problems

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

Hyper-Differential Sensitivity Analysis of Inverse Problems Governed by PDEs

Hyper-differential sensitivity analysis with respect to model discrepancy

Stochastic Deep Model Reference Adaptive Control

Hyper-differential sensitivity analysis for model form error

Characterizing Approximation Methods for Digital Twins in Scientific Computing

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

Goal-oriented data-driven reduced-order modeling guided by hyper-differential sensitivity analysis

Trajectory Planning for Aerospace Vehicles using Deep Reinforcement Learning

Bedrock Inversion and Hyper Differential Sensitivity Analysis for the Shallow Ice Model

Parallel Solver Framework for Mixed-Integer PDE-Constrained Optimization

A Fast Solver for the Fractional Helmholtz Equation

Hyper-Differential Sensitivity Analysis: Managing High Dimensional Uncertainty in Large-Scale Optimization Problems

Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection

Hyper-differential sensitivity analysis of PDE-constrained inverse problems

Peridynamics to Predict Fracturing in the Subsurface

Efficient Training of Neural Network Surrogate Methods with Variable Projection