Learning Thermodynamically Stable and Galilean Invariant Partial Differential Equations for Non-equilibrium Flows

28 September 2020

Papers citing "Learning Thermodynamically Stable and Galilean Invariant Partial Differential Equations for Non-equilibrium Flows"

7 / 7 papers shown

Title
Structure-preserving neural networks for the regularized entropy-based closure of the Boltzmann moment system Steffen Schotthöfer M. P. Laiu Martin Frank C. Hauck 27 0 0 22 Apr 2024
DeePN $^2$ : A deep learning-based non-Newtonian hydrodynamic model Lidong Fang Pei Ge Lei Zhang Weinan E null Huan Lei 11 8 0 29 Dec 2021
Machine learning moment closure models for the radiative transfer equation III: enforcing hyperbolicity and physical characteristic speeds Juntao Huang Yingda Cheng Andrew J. Christlieb L. Roberts AI4CE 20 15 0 02 Sep 2021
Machine learning moment closure models for the radiative transfer equation II: enforcing global hyperbolicity in gradient based closures Juntao Huang Yingda Cheng Andrew J. Christlieb L. Roberts W. Yong AI4CE 13 18 0 30 May 2021
Machine learning moment closure models for the radiative transfer equation I: directly learning a gradient based closure Juntao Huang Yingda Cheng Andrew J. Christlieb L. Roberts AI4CE 13 26 0 12 May 2021
Data-driven discovery of multiscale chemical reactions governed by the law of mass action Juntao Huang Y. Zhou W. Yong 23 5 0 17 Jan 2021
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 178 598 0 22 Sep 2016