2 citations · 2 across the 3 of their papers we have counts for
3 papers
Probabilistic transfer learning methodology to expedite high fidelity simulation of reactive flows
Bruno S. Soriano, Ki Sung Jung, Tarek Echekki +2
Reduced order models based on the transport of a lower dimensional manifold representation of the thermochemical state, such as Principal Component (PC) transport and Machine Learn…
Machine Learning Techniques for Data Reduction of CFD Applications
Jaemoon Lee, Ki Sung Jung, Qian Gong +5
We present an approach called guaranteed block autoencoder that leverages Tensor Correlations (GBATC) for reducing the spatiotemporal data generated by computational fluid dynamics…
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…