Data-assisted combustion simulations with dynamic submodel assignment using random forests. - Wai Tong Chung; Aashwin Ananda Mishra; Nikolaos Perakis; Matthias Ihme (CoRR, 2020)

Accelerating High-fidelity Combustion Simulations with Classification Algorithms. - Wai Tong Chung; Aashwin Ananda Mishra; Nikolaos Perakis; Matthias Ihme (AAAI Spring Symposium: MLPS, 2021)

Interpretable Data-driven Methods for Subgrid-scale Closure in LES for Transcritical LOX/GCH4 Combustion. - Wai Tong Chung; Aashwin Ananda Mishra; Matthias Ihme (CoRR, 2021)

The Bearable Lightness of Big Data: Towards Massive Public Datasets in Scientific Machine Learning. - Wai Tong Chung; Ki Sung Jung; Jacqueline H. Chen; Matthias Ihme (CoRR, 2022)

Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data. - Wai Tong Chung; Bassem Akoush; Pushan Sharma; Alex Tamkin; Ki Sung Jung; Jacqueline Chen; Jack Guo; Davy Brouzet; Mohsen Talei; Bruno Savard; Alexei Y. Poludnenko; Matthias Ihme (NeurIPS, 2023)

A Staged Deep Learning Approach to Spatial Refinement in 3D Temporal Atmospheric Transport. - M. Giselle Fernández-Godino; Wai Tong Chung; Akshay A. Gowardhan; Matthias Ihme; Qingkai Kong; Donald D. Lucas; Stephen C. Myers (CoRR, 2024)