Scheduled presentations:

• Accounting for elasto-plasticity in constitutive artificial neural networks
  B. Boes (University of Wuppertal), *J. Simon (University of Wuppertal), H. Holthusen (RWTH Aachen University)
• Surrogate Elements for Nonlinear Microstructures using Physics-enhanced Machine Learning
  *W. Li (TU Darmstadt), O. Weeger (TU Darmstadt)
• An automated dual-stage approach for constitutive modeling of hyperelastic solids
  *L. Linden (TU Dresden), K. Kalina (TU Dresden), J. Brummund (TU Dresden), M. Kästner (TU Dresden)
• Physics-enhanced neural networks for hyperelastic beam modeling
  *J. Schommartz (Technical University of Darmstadt), J. Alzate Cobo (Technical University of Darmstadt), D. Klein (Technical University of Darmstadt), O. Weeger (Technical University of Darmstadt)
• Graph Neural Networks with Embedded Symmetries for Robust Computational Homogenization of Metamaterials
  *F. Hendriks (Eindhoven University of Technology), V. Menkovski (Eindhoven University of Technology), M. Doškář (2Czech Technical University in Prague), M. Geers (Eindhoven University of Technology), O. Rokoš (Eindhoven University of Technology)
• A physically recurrent neural network for rate dependent composite materials
  *M. Maia (Delft University of Technology), I. Rocha (Delft University of Technology), D. Kovačević (Delft University of Technology), F. van der Meer (Delft University of Technology)