Scheduled presentations:

• A Physics-Informed Convolutional Neural Network with Variational Regularization for Diffusion in Heterogeneous Media
  *Z. Han (University of Gothenburg), M. Mirkhalaf (University of Gothenburg)
• Efficient Graph Design for GNN Surrogates of Flexible Unstructured Coastal Models in Complex Geometries
  *F. Schäfer (DHI A/S), C. Cremer (DHI A/S), J. Mariegaard (DHI A/S)
• Data-Calibrated Simulations of Photoresist Photoreactions via Physics-Informed Neural Operators
  *C. Straub (Fraunhofer IISB), T. Santos (Fraunhofer IISB), Y. Singh (Fraunhofer IISB), A. Erdmann (Fraunhofer IISB), A. Rosskopf (Fraunhofer IISB)
• Dimensionally Reduced Depth-Encoded Surrogate Modelling for Fully Stressed Cantilever Beam Profile design
  *C. D R (Indian Institute of Technology Palakkad), N. Muthu (Indian Institute of Technology Palakkad)
• Reliable Forecasting via Physics-Guided Stochastic Augmentation
  *X. Wu (Southern University of Science and Technology), K. Wu (Southern University of Science and Technology)
• Quantitative Analysis of Granular Object Distributions Using Deep Learning–Based Image Segmentation
  *A. Jleli (Université du Québec Abitibi-Témiscamingue)