Scheduled presentations:

• Keynote Equivariant neural networks with applications to constitutive modeling
  K. Garanger (University of California, Irvine), *J. Rimoli (University of California, Irvine)
• Orientation-aware interaction-based deep material network for polycrystalline materials with diverse microstructures
  *T. Wei (National Taiwan University), W. Wan (National Taiwan University), C. Chen (National Taiwan University)
• Strengthening Deep Material Networks with Offline Training Using Local Field Data
  *D. Shin (POSTECH), R. Lebensohn (Los Alamos National Laboratory), R. Dingreville (Sandia National Laboratories)
• AI-Driven Elastoplastic Bone Model Considering Biological Variability for Automotive Safety
  *C. Saenz-Betancourt (Ludwig-Maximilians-Universität & BMW Group), D. Draper (BMW Group), P. Wernicke (BMW Group), F. Duddeck (Technical University of Munich), S. Peldschus (Ludwig-Maximilians-Universität München)
• A Machine Learning-Based Method for Deriving Explicit Formulas for Stress Evaluation, Sizing, and Strength Assessment in Pressure Vessel Design
  *P. AMUZUGA (CETIM)