43 citations · 48 across the 4 of their papers we have counts for
4 papers
Deep learning-based predictive modelling of transonic flow over an aerofoil
Li-Wei Chen, Nils Thuerey
Effectively predicting transonic unsteady flow over an aerofoil poses inherent challenges. In this study, we harness the power of deep neural network (DNN) models using the attenti…
Symmetric Basis Convolutions for Learning Lagrangian Fluid Mechanics
Rene Winchenbach, Nils Thuerey
Learning physical simulations has been an essential and central aspect of many recent research efforts in machine learning, particularly for Navier-Stokes-based fluid mechanics. Cl…
Physics-Preserving AI-Accelerated Simulations of Plasma Turbulence
Robin Greif, Frank Jenko, Nils Thuerey
Turbulence in fluids, gases, and plasmas remains an open problem of both practical and fundamental importance. Its irreducible complexity usually cannot be tackled computationally…
Learning to Control PDEs with Differentiable Physics
Philipp Holl, Vladlen Koltun, Nils Thuerey
Predicting outcomes and planning interactions with the physical world are long-standing goals for machine learning. A variety of such tasks involves continuous physical systems, wh…