Hybrid Model of Mathematical and Neural Network Formulations for Rolling Force and Temperature Prediction in Hot Rolling Processes. - Rakhoon Hwang; Hyeontae Jo; Kyung Seok Kim; Hyung Ju Hwang (IEEE Access, 2020)

Trend to equilibrium for the kinetic Fokker-Planck equation via the neural network approach. - Hyung Ju Hwang; Jin Woo Jang; Hyeontae Jo; Jae Yong Lee 002 (J. Comput. Phys., 2020)

Deep neural network approach to forward-inverse problems. - Hyeontae Jo; Hwijae Son; Hyung Ju Hwang; Eun Heui Kim (Networks Heterog. Media, 2020)

Development of patients triage algorithm from nationwide COVID-19 registry data based on machine learning. - Hyung Ju Hwang; Seyoung Jung; Min Sue Park; Hyeontae Jo (CoRR, 2021)

Estimation of System Parameters Including Repeated Cross-Sectional Data through Emulator-Informed Deep Generative Model. - Hyunwoo Cho; Sung Woong Cho; Hyeontae Jo; Hyung Ju Hwang (CoRR, 2024)

Density physics-informed neural networks reveal sources of cell heterogeneity in signal transduction. - Hyeontae Jo; Hyukpyo Hong; Hyung Ju Hwang; Won Chang; Jae Kyoung Kim (Patterns, 2024)

Estimating the distribution of parameters in differential equations with repeated cross-sectional data. - Hyeontae Jo; Sung Woong Cho; Hyung Ju Hwang (PLoS Comput. Biol., 2024)

SymScore: Machine learning accuracy meets transparency in a symbolic regression-based clinical score generator. - Olive R. Cawiding; Sieun Lee; Hyeontae Jo; Sungmoon Kim; Sooyeon Suh; Eun Yeon Joo; Seockhoon Chung; Jae Kyoung Kim (Comput. Biol. Medicine, 2025)

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals. - Hyeontae Jo; Kresimir Josic; Jae Kyoung Kim (CoRR, 2025)

Learning from Imperfect Data: Robust Inference of Dynamic Systems using Simulation-based Generative Model. - Hyunwoo Cho; Hyeontae Jo; Hyung Ju Hwang (CoRR, 2025)