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05/04/2023
Multilevel Monte Carlo estimators for derivative-free optimization under uncertainty
Optimization is a key tool for scientific and engineering applications, ...
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11/20/2022
Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification
Multi-fidelity Monte Carlo methods leverage low-fidelity and surrogate m...
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08/03/2022
Neural Nets with a Newton Conjugate Gradient Method on Multiple GPUs
Training deep neural networks consumes increasing computational resource...
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04/08/2022
Active-learning-based non-intrusive Model Order Reduction
The Model Order Reduction (MOR) technique can provide compact numerical ...
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09/29/2021
preCICE v2: A Sustainable and User-Friendly Coupling Library
preCICE is a free/open-source coupling library. It enables creating part...
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03/25/2021
Model Order Reduction based on Runge-Kutta Neural Network
Model Order Reduction (MOR) methods enable the generation of real-time-c...
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02/25/2021
Machine Learning-Based Optimal Mesh Generation in Computational Fluid Dynamics
Computational Fluid Dynamics (CFD) is a major sub-field of engineering. ...
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10/26/2020
Resiliency in Numerical Algorithm Design for Extreme Scale Simulations
This work is based on the seminar titled “Resiliency in Numerical Algori...
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01/08/2020
Quasi-Newton Waveform Iteration for Partitioned Fluid-Structure Interaction
We present novel coupling schemes for partitioned multi-physics simulati...
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10/27/2019
Fast Evaluation and Approximation of the Gauss-Newton Hessian Matrix for the Multilayer Perceptron
We introduce a fast algorithm for entry-wise evaluation of the Gauss-New...
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11/30/2018
Sensitivity-driven adaptive sparse stochastic approximations in plasma microinstability analysis
Quantifying uncertainty in predictive simulations for real-world problem...
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07/02/2018
Computational steering of complex flow simulations
Computational Steering, the combination of a simulation back-end with a ...
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11/16/2010