Permeability Prediction of Porous Media using Convolutional Neural Networks with Physical Properties. - Hongkyu Yoon; Darryl J. Melander; Stephen J. Verzi (AAAI Spring Symposium: MLPS, 2020)

Connectivity-informed Drainage Network Generation using Deep Convolution Generative Adversarial Networks. - Sung Eun Kim; Yongwon Seo 002; Junshik Hwang; Hongkyu Yoon; Jonghyun Lee 005 (CoRR, 2020)

Fast and Scalable Earth Texture Synthesis using Spatially Assembled Generative Adversarial Neural Networks. - Sung Eun Kim; Hongkyu Yoon; Jonghyun Lee 005 (CoRR, 2020)

Machine Learning Application for Permeability Estimation of Three-Dimensional Rock Images. - Hongkyu Yoon; Darryl J. Melander; Stephen J. Verzi (AAAI Spring Symposium: MLPS, 2021)

Applications of physics-informed scientific machine learning in subsurface science: A survey. - Alexander Y. Sun; Hongkyu Yoon; Chung-Yan Shih; Zhi Zhong (CoRR, 2021)

Neurodynamical Role of STDP in Storage and Retrieval of Associative Information. - Hongkyu Yoon; Pilwon Kim (CoRR, 2021)

Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: comparison with linear subspace techniques. - Teeratorn Kadeethum; Francesco Ballarin; Youngsoo Choi; Daniel O'Malley; Hongkyu Yoon; Nikolaos Bouklas (CoRR, 2021)

Machine Learning in Heterogeneous Porous Materials. - Marta D'Elia; Hang Deng; Cedric G. Fraces; Krishna C. Garikipati; Lori Graham-Brady; Amanda A. Howard; George Em Karniadakis; Vahid Keshavarzzadeh; Robert M. Kirby; J. Nathan Kutz; Chunhui Li; Xing Liu; et al. (CoRR, 2022)

Reduced order modeling with Barlow Twins self-supervised learning: Navigating the space between linear and nonlinear solution manifolds. - Teeratorn Kadeethum; Francesco Ballarin; Daniel O'Malley; Youngsoo Choi; Nikolaos Bouklas; Hongkyu Yoon (CoRR, 2022)

Deep Convolutional Ritz Method: Parametric PDE surrogates without labeled data. - Jan Niklas Fuhg; Arnav Karmarkar; Teeratorn Kadeethum; Hongkyu Yoon; Nikolaos Bouklas (CoRR, 2022)

Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties. - Teeratorn Kadeethum; Daniel O'Malley; Youngsoo Choi; Hari S. Viswanathan; Nikolaos Bouklas; Hongkyu Yoon (Comput. Geosci., 2022)

Epistemic Uncertainty-Aware Barlow Twins Reduced Order Modeling for Nonlinear Contact Problems. - Teeratorn Kadeethum; John D. Jakeman; Youngsoo Choi; Nikolaos Bouklas; Hongkyu Yoon (IEEE Access, 2023)

Subsurface Characterization using Ensemble-based Approaches with Deep Generative Models. - Jichao Bao; Hongkyu Yoon; Jonghyun Lee 005 (CoRR, 2023)

Progressive reduced order modeling: empowering data-driven modeling with selective knowledge transfer. - Teeratorn Kadeethum; Daniel O'Malley; Youngsoo Choi; Hari S. Viswanathan; Hongkyu Yoon (CoRR, 2023)

Efficient machine-learning surrogates for large-scale geological carbon and energy storage. - Teeratorn Kadeethum; Stephen J. Verzi; Hongkyu Yoon (CoRR, 2023)