Typhoon track prediction using satellite images in a Generative Adversarial Network. - Mario Rüttgers; Sangseung Lee; Donghyun You (CoRR, 2018)

Prediction of Acoustic Fields Using a Lattice-Boltzmann Method and Deep Learning. - Mario Rüttgers; Seong-Ryong Koh; Jenia Jitsev; Wolfgang Schröder 001; Andreas Lintermann (ISC Workshops, 2020)

Machine-Learning-Based Control of Perturbed and Heated Channel Flows. - Mario Rüttgers; Moritz Waldmann; Wolfgang Schröder 001; Andreas Lintermann (ISC Workshops, 2021)

Effects of the Nasal Cavity Complexity on the Pharyngeal Airway Fluid Mechanics: A Computational Study. - Hussein Aljawad; Mario Rüttgers; Andreas Lintermann; Wolfgang Schröder 001; Kyungmin Clara Lee (J. Digit. Imaging, 2021)

Prediction of Typhoon Track and Intensity Using a Generative Adversarial Network With Observational and Meteorological Data. - Mario Rüttgers; Soohwan Jeon; Sangseung Lee; Donghyun You (IEEE Access, 2022)

A machine-learning-based method for automatizing lattice-Boltzmann simulations of respiratory flows. - Mario Rüttgers; Moritz Waldmann; Wolfgang Schröder 001; Andreas Lintermann (Appl. Intell., 2022)

How Regional Wind Characteristics Affect CNN-based wind predictions: Insights from Spatiotemporal Correlation Analysis. - Heesoo Shin; Mario Rüttgers; Sangseung Lee (CoRR, 2023)

Parallel Reinforcement Learning and Gaussian Process Regression for Improved Physics-Based Nasal Surgery Planning. - Mario Rüttgers; Fabian Hübenthal; Makoto Tsubokura; Andreas Lintermann (PPAM (3), 2024)

Automated surgery planning for an obstructed nose by combining computational fluid dynamics with reinforcement learning. - Mario Rüttgers; Moritz Waldmann; Klaus Vogt; Justus Ilgner; Wolfgang Schröder 001; Andreas Lintermann (Comput. Biol. Medicine, 2024)

Robustness evaluation of large-scale machine learning-based reduced order models for reproducing flow fields. - Aito Higashida; Kazuto Ando; Mario Rüttgers; Andreas Lintermann; Makoto Tsubokura (Future Gener. Comput. Syst., 2024)

Refining computer tomography data with super-resolution networks to increase the accuracy of respiratory flow simulations. - Xin Liu; Mario Rüttgers; Alessio Quercia; Romain Egele; Elisabeth Pfaehler; Rushikesh Shende; Marcel Aach; Wolfgang Schröder 001; Prasanna Balaprakash; Andreas Lintermann (Future Gener. Comput. Syst., 2024)

On the choice of physical constraints in artificial neural networks for predicting flow fields. - Rishabh Puri; Junya Onishi; Mario Rüttgers; Rakesh Sarma; Makoto Tsubokura; Andreas Lintermann (Future Gener. Comput. Syst., 2024)

Patient-specific lattice-Boltzmann simulations with inflow conditions from magnetic resonance velocimetry measurements for analyzing cerebral aneurysms. - Mario Rüttgers; Moritz Waldmann; Shota Ito; Carolin Wüstenhagen; Sven Grundmann; Martin Brede; Andreas Lintermann (Comput. Biol. Medicine, 2025)

Towards a widespread usage of computational fluid dynamics simulations for automated virtual nasal surgery planning. - Mario Rüttgers; Moritz Waldmann; Fabian Hübenthal; Klaus Vogt; Makoto Tsubokura; Sangseung Lee; Andreas Lintermann (Future Gener. Comput. Syst., 2026)