31 citations · 41 across the 7 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
physics.chem-ph2023★ 2 cited
Transfer learning for predicting source terms of principal component transport in chemically reactive flow
Ki Sung Jung, Tarek Echekki, Jacqueline H. Chen +1
The objective of this study is to evaluate whether the number of requisite training samples can be reduced with the use of various transfer learning models for predicting, for exam…
physics.chem-ph2023★ 1 cited
A Framework for Combustion Chemistry Acceleration with DeepONets
Anuj Kumar, Tarek Echekki
A combustion chemistry acceleration scheme is developed based on deep operator networks (DeepONets). The scheme is based on the identification of combustion reaction dynamics throu…