Keynote speakers

• Martin Eigel
  (WIAS, Germany)
  "A Statistical Learning Approach for Parametric PDEs"
• Ahmed Elsheikh
  (Heriot Watt University, UK)
  "Machine Learning Approaches for Uncertainty Quantification of Subsurface Flow Models"
• Jan Hesthaven
  (EPFL, Switzerland)
  "On the Use of Machine Learning in Computational Science and Engineering"
• Desmond Higham
  (University of Strathclyde, UK)
  "Numerical Precision in Deep Learning"
• Jakub Marecek
  (IBM Dublin, Ireland)
  "Scaling Up Deep Learning for PDE-based Models"
• Kaj Nyström
  (Uppsala University, Sweden)
  "Some Thoughts on Neural Networks, PDEs and Data-Driven Discovery"
• Philipp Petersen
  (University of Oxford, UK)
  "Challenges and Opportunities for Numerical Solvers of PDEs Based on Deep Neural Networks"

Contributed talks

• Markus Geveler
  (TU Dortmund, Germany)
  "Machine Learning Approaches for the Acceleration of the Linear Solver in PDE Simulations"
• Jim Magiera
  (University of Stuttgart, Germany)
  "Constraint-Aware Neural Networks for Riemann Problems"
• Yufei Zhang
  (University of Oxford, UK)
  "Rectified Deep Neural Networks Overcome the Curse of Dimensionality forNonsmooth Value Functions in Zero-Sum Games of Nonlinear Stiff Systems"