Merten Stender

According to our database, Merten Stender authored at least 11 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Bridging ocean wave physics and deep learning: Physics-informed neural operators for nonlinear wavefield reconstruction in real-time.

Svenja Ehlers, Merten Stender, Norbert P. Hoffmann

CoRR, August, 2025

Dynamics-Informed Reservoir Computing with Visibility Graphs.

Charlotte Geier, Merten Stender

CoRR, July, 2025

Denoising and Reconstruction of Nonlinear Dynamics using Truncated Reservoir Computing.

Omid Sedehi, Manish Yadav, Merten Stender, Sebastian Oberst

CoRR, April, 2025

Physics-informed neural networks for phase-resolved data assimilation and prediction of nonlinear ocean waves.

Svenja Ehlers, Norbert P. Hoffmann, Tianning Tang, Adrian H. Callaghan, Rui Cao, Enrique M. Padilla, Yuxin Fang, Merten Stender

CoRR, January, 2025

2024

The impact of AI on engineering design procedures for dynamical systems.

Kristin Miriam de Payrebrune, Kathrin Flaßkamp, Tom Ströhla, Thomas Sattel, Dieter Bestle, Benedict Röder, Peter Eberhard, Sebastian Peitz, Marcus Stoffel, Rutwik Gulakala, Aditya Borse, Meike Wohlleben, Walter Sextro, Maximilian Raff, C. David Remy, Manish Yadav, Merten Stender, Jan van Delden, Timo Lüddecke, Sabine C. Langer, Julius Schultz, Christopher Blech

CoRR, 2024

Data Publishing in Mechanics and Dynamics: Challenges, Guidelines, and Examples from Engineering Design.

Henrik Ebel, Jan van Delden, Timo Lüddecke, Aditya Borse, Rutwik Gulakala, Marcus Stoffel, Manish Yadav, Merten Stender, Leon Schindler, Kristin Miriam de Payrebrune, Maximilian Raff, C. David Remy, Benedict Röder, Peter Eberhard

CoRR, 2024

Data assimilation and parameter identification for water waves using the nonlinear Schrödinger equation and physics-informed neural networks.

Svenja Ehlers, Niklas A. Wagner, Annamaria Scherzl, Marco Klein, Norbert P. Hoffmann, Merten Stender

CoRR, 2024

2023

Data-driven reduced order modeling for mechanical oscillators using Koopman approaches.

Charlotte Geier, Merten Stender, Norbert P. Hoffmann

Frontiers Appl. Math. Stat., 2023

Machine learning for phase-resolved reconstruction of nonlinear ocean wave surface elevations from sparse remote sensing data.

Svenja Ehlers, Marco Klein, Alexander Heinlein, Mathies Wedler, Nicolas Desmars, Norbert P. Hoffmann, Merten Stender

CoRR, 2023

2022

Surface similarity parameter: A new machine learning loss metric for oscillatory spatio-temporal data.

Mathies Wedler, Merten Stender, Marco Klein, Svenja Ehlers, Norbert P. Hoffmann

Neural Networks, 2022

2020

Deep learning for brake squeal: vibration detection, characterization and prediction.

Merten Stender, Merten Tiedemann, David Spieler, Daniel Schoepflin, Norbert P. Hoffmann, Sebastian Oberst

CoRR, 2020