Dear all,

The next speaker in our Seminar for machine learning and UQ in scientific computing will be Nils Thuerey, associate-professor at the TU Munich. He will talk about creating probabilistic surrogates using diffusion models and differentiable solvers, see the abstract below. The talk will take place at 11AM CET. For those at CWI, the location will be L017 and a Zoom link is attached for online attendees.

Kind regards,

Wouter Edeling

Join Zoom Meeting https://cwi-nl.zoom.us/j/84894449753?pwd=Z3VYY2sxVEJDdDJMdUhmcGwyUXdzUT09

Meeting ID: 848 9444 9753 Passcode: 631919

28 March 2024 11h00 CET, Nils Thuerey, Probabilistic Fluid Simulations: Diffusion Models & Differentiable Solvers

This talk focuses on the possibilities that arise from recent advances in the area of deep learning for physics simulations. In particular, it will focus on diffusion modeling and numerical solvers which are differentiable. These solvers provide crucial information for deep learning tasks in the form of gradients, which are especially important for time-dependent processes. Also, existing numerical methods for efficient solvers can be leveraged within learning tasks. This paves the way for hybrid solvers in which traditional methods work alongside pre-trained neural network components. In this context, diffusion models and score matching will be discussed as powerful building blocks for training probabilistic surrogates. The capabilities of the resulting methods will be illustrated with examples such as wake flows and turbulent flow cases.