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Bart G. van Bloemen Waanders
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2020 – today
- 2024
- [i10]Joseph Hart, Bart G. van Bloemen Waanders
:
Hyper-differential sensitivity analysis with respect to model discrepancy: Posterior Optimal Solution Sampling. CoRR abs/2402.10957 (2024) - [i9]Timbwaoga A. J. Ouermi, Jixian Li, Zachary Morrow, Bart G. van Bloemen Waanders, Christopher R. Johnson:
Glyph-Based Uncertainty Visualization and Analysis of Time-Varying Vector Fields. CoRR abs/2409.00042 (2024) - 2023
- [j14]Joseph L. Hart
Sensitivity-Driven Experimental Design to Facilitate Control of Dynamical Systems. J. Optim. Theory Appl. 196(3): 855-881 (2023) - [j13]Joseph L. Hart
Enabling Hyper-Differential Sensitivity Analysis for Ill-Posed Inverse Problems. SIAM J. Sci. Comput. 45(4): 1947- (2023) - 2022
- [i8]Isaac Sunseri, Alen Alexanderian, Joseph L. Hart, Bart G. van Bloemen Waanders:
Hyper-differential sensitivity analysis for nonlinear Bayesian inverse problems. CoRR abs/2202.02219 (2022) - [i7]Wolfgang Bangerth, Chris R. Johnson, Dennis K. Njeru, Bart G. van Bloemen Waanders:
Estimating and using information in inverse problems. CoRR abs/2208.09095 (2022) - [i6]Joseph L. Hart, Bart G. van Bloemen Waanders
Hyper-differential sensitivity analysis with respect to model discrepancy: mathematics and computation. CoRR abs/2210.09037 (2022) - [i5]Joseph L. Hart, Bart G. van Bloemen Waanders
Hyper-differential sensitivity analysis with respect to model discrepancy: Calibration and optimal solution updating. CoRR abs/2210.09044 (2022) - 2021
- [j12]Arvind K. Saibaba
Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis. Numer. Linear Algebra Appl. 28(4) (2021) - [j11]Christian Glusa
A Fast Solver for the Fractional Helmholtz Equation. SIAM J. Sci. Comput. 43(2): A1362-A1388 (2021) - [j10]Elizabeth Newman, Lars Ruthotto
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection. SIAM J. Math. Data Sci. 3(4): 1041-1066 (2021) - [c5]Girish Joshi, Girish Chowdhary, Bart G. van Bloemen Waanders
Stochastic Deep Model Reference Adaptive Control. CDC 2021: 1075-1082 - [i4]Joseph L. Hart, Bart G. van Bloemen Waanders:
Enabling and interpreting hyper-differential sensitivity analysis for Bayesian inverse problems. CoRR abs/2106.11813 (2021) - 2020
- [i3]Arvind K. Saibaba, Joseph L. Hart, Bart G. van Bloemen Waanders:
Randomized Algorithms for Generalized Singular Value Decomposition with Application to Sensitivity Analysis. CoRR abs/2002.02812 (2020) - [i2]Elizabeth Newman, Lars Ruthotto, Joseph L. Hart, Bart G. van Bloemen Waanders:
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection. CoRR abs/2007.13171 (2020)
2010 – 2019
- 2019
- [i1]Chester J. Weiss, Bart G. van Bloemen Waanders, Harbir Antil:
Fractional Operators Applied to Geophysical Electromagnetics. CoRR abs/1902.05096 (2019) - 2014
- [j9]Irina Kalashnikova, Matthew F. Barone, Srinivasan Arunajatesan, Bart G. van Bloemen Waanders
Construction of energy-stable projection-based reduced order models. Appl. Math. Comput. 249: 569-596 (2014) - [j8]Drew P. Kouri
Inexact Objective Function Evaluations in a Trust-Region Algorithm for PDE-Constrained Optimization under Uncertainty. SIAM J. Sci. Comput. 36(6) (2014) - 2013
- [j7]Drew P. Kouri
A Trust-Region Algorithm with Adaptive Stochastic Collocation for PDE Optimization under Uncertainty. SIAM J. Sci. Comput. 35(4) (2013) - 2012
- [j6]Kevin R. Long, Paul T. Boggs, Bart G. van Bloemen Waanders:
Sundance: High-level software for PDE-constrained optimization. Sci. Program. 20(3): 293-310 (2012) - 2011
- [j5]H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judith Hill
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations. SIAM J. Sci. Comput. 33(1): 407-432 (2011) - 2010
- [j4]Kevin R. Long, Robert C. Kirby
Unified Embedded Parallel Finite Element Computations via Software-Based Fr[e-acute]chet Differentiation. SIAM J. Sci. Comput. 32(6): 3323-3351 (2010)
2000 – 2009
- 2008
- [j3]Roscoe A. Bartlett, Bart G. van Bloemen Waanders, Martin Berggren
Hybrid differentiation strategies for simulation and analysis of applications in C++. ACM Trans. Math. Softw. 35(1): 1:1-1:29 (2008) - 2007
- [j2]Tan Bui-Thanh
Goal-oriented, model-constrained optimization for reduction of large-scale systems. J. Comput. Phys. 224(2): 880-896 (2007) - [c4]Omar Bashir, Omar Ghattas, Judith Hill
Hessian-Based Model Reduction for Large-Scale Data Assimilation Problems. International Conference on Computational Science (1) 2007: 1010-1017 - 2006
- [c3]Volkan Akcelik, George Biros, Andrei Draganescu, Omar Ghattas, Judith Hill
Inversion of Airborne Contaminants in a Regional Model. International Conference on Computational Science (3) 2006: 481-488 - [p1]Volkan Akçelik, George Biros, Omar Ghattas, Judith Hill, David E. Keyes, Bart G. van Bloemen Waanders:
Parallel Algorithms for PDE-Constrained Optimization. Parallel Processing for Scientific Computing 2006: 291-322 - 2005
- [c2]Karen Willcox, Omar Ghattas, Bart G. van Bloemen Waanders
An Optimization Frame work for Goal-Oriented, Model-Based Reduction of Large-Scale Systems. CDC/ECC 2005: 2265-2271 - [c1]Volkan Akcelik, George Biros, Andrei Draganescu, Judith Hill
Dynamic Data-Driven Inversion For Terascale Simulations: Real-Time Identification Of Airborne Contaminants. SC 2005: 43 - 2004
- [j1]Roscoe A. Bartlett, Bart G. van Bloemen Waanders
Vector reduction/transformation operators. ACM Trans. Math. Softw. 30(1): 62-85 (2004)
Coauthor Index
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