Pages that link to "Item:Q2135258"

The following pages link to Machine learning moment closure models for the radiative transfer equation. I: Directly learning a gradient based closure (Q2135258):

Displaying 8 items.

• Neural-network based collision operators for the Boltzmann equation (Q2083624) (← links)
• A neural network closure for the Euler-Poisson system based on kinetic simulations (Q2122778) (← links)
• Machine learning moment closure models for the radiative transfer equation. III: enforcing hyperbolicity and physical characteristic speeds (Q2680325) (← links)
• Learning invariance preserving moment closure model for Boltzmann-BGK equation (Q2699490) (← links)
• Machine Learning Approaches for the Inversion of the Radiative Transfer Equation (Q5302449) (← links)
• Machine Learning Moment Closure Models for the Radiative Transfer Equation II: Enforcing Global Hyperbolicity in Gradient-Based Closures (Q6109133) (← links)
• Machine learning moment closure models for the radiative transfer equation I: directly learning a gradient based closure (Q6367497) (← links)
• A Variable Eddington Factor Model for Thermal Radiative Transfer with Closure Based on Data-Driven Shape Function (Q6571973) (← links)