85 citations · 176 across the 4 of their papers we have counts for
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cs.CE2021★ 24 cited
Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties
T. Kadeethum, D. O'Malley, Y. Choi +3
Machine learning-based data-driven modeling can allow computationally efficient time-dependent solutions of PDEs, such as those that describe subsurface multiphysical problems. In…
cs.CE2021★ 67 cited
Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: comparison with linear subspace techniques
T. Kadeethum, F. Ballarin, Y. Choi +3
Natural convection in porous media is a highly nonlinear multiphysical problem relevant to many engineering applications (e.g., the process of sequestration). Here,…