1. Wolf, T., Riegler, T., Vaudrevange, P.K.S., Rößler, T., Fäßler, V., Keckeisen, M., Beutenmüller, F., Kriwet, A., Kohler, J., Springmann, P., Gutsche, R., Nyfantis, N., Giannoukos, K., Shehaj, F.: “AI-aided simulation – the future of NVH engineering.” Poster presented on 23. Internationales Stuttgarter Symposium, 2023.
2. Mandl, A., Barzen, J., Bechtold, M., Keckeisen, M., Leymann, F., Vaudrevange, P.K.S.: “Linear Structure of Training Samples in Quantum Neural Network Applications.” In: Monti, F., et al. Service-Oriented Computing – ICSOC 2023 Workshops. ICSOC 2023. Lecture Notes in Computer Science, vol 14518. Springer, Singapore. https://doi.org/10.1007/978-981-97-0989-2_12
3. Wolf, T., Keckeisen, M., Beutenmüller, F., Rößler, T., Nyfantis, D., Giannoukos, K., Shehaj, F.: “CubicAI – A Demonstrator for the AI-Aided Design of Dynamical Systems Featuring the Development of Car Suspension Systems”, Demonstrator at the Digital Product Forum 2022, see https://cubicai.twt-gmbh.de/home and https://twt-innovation.de/ .
4. Bannerjee, R., Stasinou, M.-E., Vaudrevange, P., Kraus, H., Rößler, T., Keckeisen, M., V. Faessler, V.: “Accelerating Simulations using Hybrid Quantum-Classical Machine Learning.” SimTech2023.
5. “MODELISAR: From System Modeling to S/W running on the Vehicle”, see https://itea4.org/project/modelisar.html.