Mario Ohlberger | DeepAI

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Featured Co-authors

Bernard Haasdonk
27 publications
Barbara Kaltenbacher
21 publications
Christian Engwer
18 publications
Tizian Wenzel
12 publications
Tim Keil
11 publications
Oliver Sander
11 publications
Oleg Iliev
10 publications
Andreas Dedner
9 publications
Peter Bastian
8 publications
Felix Schindler
8 publications
Stefan Volkwein
8 publications

∙ 09/14/2023

Adaptive Reduced Basis Trust Region Methods for Parameter Identification Problems

In this contribution, we are concerned with model order reduction in the...

0 Michael Kartmann, et al. ∙

∙ 03/28/2023

An optimally stable approximation of reactive transport using discrete test and infinite trial spaces

In this contribution we propose an optimally stable ultraweak Petrov-Gal...

0 Lukas Renelt, et al. ∙

∙ 03/06/2023

Adaptive Localized Reduced Basis Methods for Large Scale Parameterized Systems

In this contribution, we introduce and numerically evaluate a certified ...

0 Tim Keil, et al. ∙

∙ 02/28/2023

Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling

In the framework of reduced basis methods, we recently introduced a new ...

0 Tizian Wenzel, et al. ∙

∙ 03/18/2022

A relaxed localized trust-region reduced basis approach for optimization of multiscale problems

In this contribution, we introduce and analyze a new relaxed and localiz...

0 Tim Keil, et al. ∙

∙ 03/11/2022

Nonlinear Model Order Reduction using Diffeomorphic Transformations of a Space-Time Domain

In many applications, for instance when describing dynamics of fluids or...

0 Hendrik Kleikamp, et al. ∙

∙ 03/03/2022

Adaptive machine learning based surrogate modeling to accelerate PDE-constrained optimization in enhanced oil recovery

In this contribution, we develop an efficient surrogate modeling framewo...

0 Tim Keil, et al. ∙

∙ 10/30/2021

Distributed model order reduction of a model for microtubule-based cell polarization using HAPOD

In this contribution we investigate in mathematical modeling and efficie...

0 Tobias Leibner, et al. ∙

∙ 10/24/2021

An adaptive model hierarchy for data-augmented training of kernel models for reactive flow

We consider machine-learning of time-dependent quantities of interest de...

0 Bernard Haasdonk, et al. ∙

∙ 05/04/2021

Model Reduction for Large Scale Systems

Projection based model order reduction has become a mature technique for...

0 Tim Keil, et al. ∙

∙ 04/06/2021

A full order, reduced order and machine learning model pipeline for efficient prediction of reactive flows

We present an integrated approach for the use of simulated data from ful...

0 Pavel Gavrilenko, et al. ∙

∙ 12/21/2020

An adaptive projected Newton non-conforming dual approach for trust-region reduced basis approximation of PDE-constrained parameter optimization

In this contribution we device and analyze improved variants of the non-...

0 Stefan Banholzer, et al. ∙

∙ 07/08/2020

A new coordinate-transformed discretization method for minimum entropy moment approximations of linear kinetic equations

In this contribution we derive and analyze a new numerical method for ki...

0 Tobias Leibner, et al. ∙

∙ 06/16/2020

A non-conforming dual approach for adaptive Trust-Region Reduced Basis approximation of PDE-constrained optimization

In this contribution we propose and rigorously analyze new variants of a...

0 Tim Keil, et al. ∙

∙ 11/04/2019

Exa-Dune – Flexible PDE Solvers, Numerical Methods and Applications

In the Exa-Dune project we have developed, implemented and optimised num...

0 Peter Bastian, et al. ∙

∙ 09/30/2019

The DUNE Framework: Basic Concepts and Recent Developments

This paper presents the basic concepts and the module structure of the D...

0 Peter Bastian, et al. ∙

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