4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.CE2023★ 4 cited
Efficient machine-learning surrogates for large-scale geological carbon and energy storage
Teeratorn Kadeethum, Stephen J. Verzi, Hongkyu Yoon
Geological carbon and energy storage are pivotal for achieving net-zero carbon emissions and addressing climate change. However, they face uncertainties due to geological factors a…
cs.LG2023
Progressive reduced order modeling: empowering data-driven modeling with selective knowledge transfer
Teeratorn Kadeethum, Daniel O'Malley, Youngsoo Choi +2
Data-driven modeling can suffer from a constant demand for data, leading to reduced accuracy and impractical for engineering applications due to the high cost and scarcity of infor…