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

Wenzel, Tizian; Haasdonk, Bernard; Kleikamp, Hendrik; Ohlberger, Mario; Schindler, Felix (2024)

In: Lirkov, I.; Margenov, S. (eds.), Large-Scale Scientific Computations, 117-125. Cham: .

Research article in edited proceedings (conference) | Peer reviewed | Published

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

Renelt, Lukas; Ohlberger, Mario; Engwer, Christian (2023)

In: Franck, Emmanuel; Fuhrmann, Jürgen;, Michel-Dansac, Victor; Navoret, Laurent (eds.), Finite Volumes for Complex Applications X—Volume 2, Hyperbolic and Related Problems, 289-298. Cham: .

Research article in edited proceedings (conference) | Peer reviewed | Published

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

Haasdonk B, Ohlberger M, Schindler F (2022)

In: Breitenecker, Felix; Kemmetmüller, Wolfgang; Körner, Andreas; Kugi, Andreas; Troch, Inge (eds.), MATHMOD 2022 Discussion Contribution Volume, 67-68. Vienna: .

Research article in edited proceedings (conference) | Peer reviewed | Published

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

In: (eds.), , -.

| Peer reviewed

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Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling Wenzel, Tizian; Haasdonk, Bernard; Kleikamp, Hendrik; Ohlberger, Mario; Schindler, Felix (2024) In: Lirkov, I.; Margenov, S. (eds.), Large-Scale Scientific Computations, 117-125. Cham: . Research article in edited proceedings (conference) \| Peer reviewed \| Published
Model Reduction and Learning for PDE Constrained Optimization Ohlberger, M.; Banholzer, S.; Haasdonk, B.; Keil, T., Kleikamp, H.; Mechelli, L.; Oguntola, M;, Schindler,F.; Volkwein, S.; Wenzel, T. (2023) In: Oberwolfach Reports, 13/2023. doi:10.4171/OWR/2023/13 Abstract in journal (conference) \| Peer reviewed \| Published
An optimally stable approximation of reactive transport using discrete test and infinite trial spaces Renelt, Lukas; Ohlberger, Mario; Engwer, Christian (2023) In: Franck, Emmanuel; Fuhrmann, Jürgen;, Michel-Dansac, Victor; Navoret, Laurent (eds.), Finite Volumes for Complex Applications X—Volume 2, Hyperbolic and Related Problems, 289-298. Cham: . Research article in edited proceedings (conference) \| Peer reviewed \| Published
A new certified hierarchical and adaptive RB-ML-ROM surrogate model for parametrized PDEs Haasdonk B, Kleikamp H, Ohlberger M, Schindler F, Wenzel T (2023) In: SIAM Journal on Scientific Computing, 45(3), A1039-1065. doi:10.1137/22M1493318 Research article (journal) \| Peer reviewed \| Published
An adaptive model hierarchy for data-augmented training of kernel models for reactive flow Haasdonk B, Ohlberger M, Schindler F (2022) In: Breitenecker, Felix; Kemmetmüller, Wolfgang; Körner, Andreas; Kugi, Andreas; Troch, Inge (eds.), MATHMOD 2022 Discussion Contribution Volume, 67-68. Vienna: . Research article in edited proceedings (conference) \| Peer reviewed \| Published
On the Performance of Machine Learning Methods for Breakthrough Curve Prediction In: .
A full order, reduced order and machine learning model pipeline for efficient prediction of reactive flows In: (eds.), , -. \| Peer reviewed