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ORCIDHyeontae Jo
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2020 – today
- 2024
[j4]Hyeontae Jo, Hyukpyo Hong
, Hyung Ju Hwang, Won Chang, Jae Kyoung Kim:
Density physics-informed neural networks reveal sources of cell heterogeneity in signal transduction. Patterns 5(2): 100899 (2024)- [i4]Hyeontae Jo, Sung Woong Cho, Hyung Ju Hwang:
Estimating the Distribution of Parameters in Differential Equations with Repeated Cross-Sectional Data. CoRR abs/2404.14873 (2024) - 2021
- [i3]Hyung Ju Hwang, Seyoung Jung, Min Sue Park, Hyeontae Jo:
Development of patients triage algorithm from nationwide COVID-19 registry data based on machine learning. CoRR abs/2109.09001 (2021) - 2020
- [j3]Rakhoon Hwang, Hyeontae Jo, Kyung Seok Kim, Hyung Ju Hwang:
Hybrid Model of Mathematical and Neural Network Formulations for Rolling Force and Temperature Prediction in Hot Rolling Processes. IEEE Access 8: 153123-153133 (2020) - [j2]Hyung Ju Hwang, Jin Woo Jang, Hyeontae Jo, Jae Yong Lee:
Trend to equilibrium for the kinetic Fokker-Planck equation via the neural network approach. J. Comput. Phys. 419: 109665 (2020) - [j1]Hyeontae Jo, Hwijae Son, Hyung Ju Hwang, Eun Heui Kim:
Deep neural network approach to forward-inverse problems. Networks Heterog. Media 15(2): 247-259 (2020)
2010 – 2019
- 2019
- [i2]Hyeontae Jo, Hwijae Son, Hyung Ju Hwang, Eunheui Kim:
Deep Neural Network Approach to Forward-Inverse Problems. CoRR abs/1907.12925 (2019) - [i1]Hyung Ju Hwang, Jin Woo Jang, Hyeontae Jo, Jae Yong Lee:
Trend to Equilibrium for the Kinetic Fokker-Planck Equation via the Neural Network Approach. CoRR abs/1911.09843 (2019)
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