Snaking bifurcations in a self-excited oscillator chain with cyclic symmetry. - Antonio Papangelo; A. Grolet; Loic Salles; Norbert P. Hoffmann; Michele Ciavarella (Commun. Nonlinear Sci. Numer. Simul., 2017)

Deep learning for brake squeal: vibration detection, characterization and prediction. - Merten Stender; Merten Tiedemann; David Spieler; Daniel Schoepflin 002; Norbert P. Hoffmann; Sebastian Oberst (CoRR, 2020)

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)

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)

Data-driven reduced order modeling for mechanical oscillators using Koopman approaches. - Charlotte Geier; Merten Stender; Norbert P. Hoffmann (Frontiers Appl. Math. Stat., 2023)

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)

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, 2025)