Scheduled presentations:

• Keynote Machine Learning for Scientific Discovery: with Examples in Fluid Mechanics
  S. Brunton*
• Veni, VINDy, Vici: a variational method to build ROMs with embedded uncertainty quantification
  P. Conti*, J. Kneifl, A. Manzoni, A. Frangi, J. Fehr, S. Brunton, N. Kutz
• Trustworthy Scientific Machine Learning with SINDy and Ensemble Learning
  U. Fasel*
• Data-Driven Sparse Sensing and Modeling Under Uncertainty
  K. Manohar*
• Neural Operator-based symbolic model discovery
  S. Garmaev*, O. Fink