37 citations · 133 across the 14 of their papers we have counts for
3 papers · 1 filter
Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations
Jae Yong Lee, Steffen Schotthöfer, Tianbai Xiao +2
This work explores the application of deep operator learning principles to a problem in statistical physics. Specifically, we consider the linear kinetic equation, consisting of a…
Neural network-based, structure-preserving entropy closures for the Boltzmann moment system
Steffen Schotthöfer, Tianbai Xiao, Martin Frank +1
This work presents neural network based minimal entropy closures for the moment system of the Boltzmann equation, that preserve the inherent structure of the system of partial diff…
A structure-preserving surrogate model for the closure of the moment system of the Boltzmann equation using convex deep neural networks
Steffen Schotthöfer, Tianbai Xiao, Martin Frank +1
Direct simulation of physical processes on a kinetic level is prohibitively expensive in aerospace applications due to the extremely high dimension of the solution spaces. In this…