Luke F. Roberts

Publication Activity (10 Years)

Years Active: 2021-2023
Publications (10 Years): 7

Top Topics

Mesh Refinement

Learning Models

Machine Learning

Previously Learned

Top Venues

J. Comput. Phys.

Multiscale Model. Simul.

Int. J. High Perform. Comput. Appl.

Publications

Philipp Grete, Joshua C. Dolence, Jonah M. Miller, Joshua Brown, Ben Ryan, Andrew Gaspar, Forrest Wolfgang Glines, Sriram Swaminarayan, Jonas Lippuner, Clell J. Solomon, Galen M. Shipman, Christoph Junghans, Daniel Holladay, James M. Stone, Luke F. Roberts
Parthenon - a performance portable block-structured adaptive mesh refinement framework. Int. J. High Perform. Comput. Appl. 37 (5) (2023)
Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts, Wen-An Yong
Machine Learning Moment Closure Models for the Radiative Transfer Equation II: Enforcing Global Hyperbolicity in Gradient-Based Closures. Multiscale Model. Simul. 21 (2) (2023)
Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts
Machine Learning Moment Closure Models for the Radiative Transfer Equation III: Enforcing Hyperbolicity and Physical Characteristic Speeds. J. Sci. Comput. 94 (1) (2023)
Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts
Machine learning moment closure models for the radiative transfer equation I: Directly learning a gradient based closure. J. Comput. Phys. 453 (2022)
Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts, Wen-An Yong
Machine learning moment closure models for the radiative transfer equation II: enforcing global hyperbolicity in gradient based closures. CoRR (2021)
Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts
Machine learning moment closure models for the radiative transfer equation I: directly learning a gradient based closure. CoRR (2021)
Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts
Machine learning moment closure models for the radiative transfer equation III: enforcing hyperbolicity and physical characteristic speeds. CoRR (2021)