Scheduled presentations:

• Deep Learning Approach for Coronary In-stent Restenosis Using Physics-informed Neural Networks
  *J. Shi (Institute of Applied Mechanics, RWTH Aachen), K. Manjunatha (Institute of Applied Mechanics, RWTH Aachen), S. Reese (Institute of Applied Mechanics, RWTH Aachen)
• Use of Machine Learning in Determining the Parameters of Viscoplastic Models
  *J. Halamka (Czech Technical University in Prague), J. Kuželka (Czech Technical University in Prague), M. Bartošák (Czech Technical University in Prague), M. Španiel (Czech Technical University in Prague)
• Inverse Design of Voxelized Architected Materials
  *X. Zheng (National Institute for Materials Science), I. Watanabe (National Institute for Materials Science)
• Towards the Identification of Crystal Plasticity Laws by Digital Twin and Machine Learning
  *D. Mesbah (CEA Saclay / Mines Paris), D. Ryckelynck (Mines Paris), H. Proudhon (Mines Paris), L. Gelebart (CEA Saclay)