Scheduled presentations:

• Towards Simulation Intelligence Testbeds: Enabling the industrial realisation of data-driven models and AI-first capabilities, and driving the evolution of computational engineering
  *A. Lavin (Pasteur Labs & ISI), J. Marecki (Pasteur Labs), J. Van de Meent (University of Amsterdam ML Lab)
• Recent Advances in PINNs
  *G. Karniadakis (Brown University)
• Solving partial differential equations with neural network bases
  *F. Dietrich (Technical University of Munich)
• Learning of integration time steps of stiff ordinary differential equations
  *U. Iben (Robert Bosch GmbH)
• Dynamic neural networks for mimetic scientific machine learning
  *W. Schilders (TU Eindhoven), C. Datar (TU Munich), F. Dietrich (TU Munich)
• Learning reduced-order models with Bayesian inference and Gaussian processes
  *M. Guo (University of Twente)