Scheduled presentations:

• A non-intrusive data-driven approach towards optimal control of electroactive polymers via dimensionality reduction
  *M. Barillas (CIMNE/UPC), A. García-González (LaCàN/UPC), R. Ortigosa (UPCT), J. Martinez-Frutos (UPCT), J. Bonet (CIMNE/UPC)
• Bayesian Calibration and Uncertainty Quantification of the Strength Models
  *J. Plohr (Los Alamos National Laboratory), D. Francom (Los Alamos National Laboratory), L. VanDervort (Los Alamos National Laboratory)
• A Novel Gradient Enhanced Gaussian Predictor Framework for the Formulation of Hyperelastic Electromechanical Models
  *N. Ellmer (Swansea University), R. Ortigosa (Technical University of Cartagena (UPCT)), J. Martínez-Frutos (Technical University of Cartagena (UPCT)), A. Gil (Swansea University)
• Rediscovering the Mullins Effect with Physics Augmented Neural Networks
  *M. Zlatić (Faculty of Engineering, University of Rijeka), M. Čanađija (Faculty of Engineering, University of Rijeka)
• Physics-augmented neural network material models for hyperelasticity with softening
  *J. Fey (TU Darmstadt), D. Klein (TU Darmstadt), O. Weeger (TU Darmstadt)
• Nonlinear Electro-Elastic Finite Element Analysis with Neural Network Constitutive Models
  *D. Klein (TU Darmstadt), R. Ortigosa (TU Cartagena), J. Martínez-Frutos (TU Cartagena), O. Weeger (TU Darmstadt)