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Multilevel Monte Carlo estimators for derivative-free optimization under uncertainty

Optimization is a key tool for scientific and engineering applications, ...

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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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Neural Nets with a Newton Conjugate Gradient Method on Multiple GPUs

Training deep neural networks consumes increasing computational resource...

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Active-learning-based non-intrusive Model Order Reduction

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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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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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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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Quasi-Newton Waveform Iteration for Partitioned Fluid-Structure Interaction

We present novel coupling schemes for partitioned multi-physics simulati...

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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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