Caglar Gürbüz

Institut: TU München, Lehrstuhl für Akustik mobiler Systeme

Beitrag

• Multi-fidelity neural network for efficient analyses of acoustic systems
• Characterization of Structural Dynamic Boundary Conditions Using Physics-Informed Neural Networks
• Probabilistic determination of frequency-dependent model parameters in acoustic material characterization