Showing results 1 to 7 of 7
A machine learning algorithm for direct detection of axion-like particle domain walls Kim, Dong Ok; Kimball, Derek F. Jackson; Masia-Roig, Hector; Smiga, Joseph A.; Wickenbrock, Arne; Budker, Dmitry; Kim, Younggeun; et al, PHYSICS OF THE DARK UNIVERSE, v.37, pp.1 - 9, 2022-09 |
Dysfunctional Beliefs and Attitudes about Sleep-6 (DBAS-6): Data-driven shortened version from a machine learning approach Jo, Hyeontae; Jeon, Hong Jun; Ahn, Junseok; Jeon, Saebom; Kim, Jae Kyoung; Chung, Seockhoon, SLEEP MEDICINE, v.119, pp.312 - 318, 2024-07 |
Gender differences in under-reporting hiring discrimination in Korea: A machine learning approach Yoon, Jaehong; Kim, Ji-Hwan; Chung, Yeonseung; Park, Jinsu; Sorensen, Glorian; Kim, Seung-Sup, Epidemiology and health, v.43, pp.1 - 10, 2021-11 |
Learning-based screening of hematologic disorders using quantitative phase imaging of individual red blood cells Kim, Geon; Jo, YoungJu; Cho, Hyungjoo; Min, Hyun-seok; Park, YongKeun, BIOSENSORS AND BIOELECTRONICS, v.123, pp.69 - 76, 2019-01 |
Machine learning assisted synthesis of lithium-ion batteries cathode materials Liow, Chi Hao; Kang, Hyeonmuk; Kim, Seunggu; Na, Moony; Lee, Yongju; Baucour, Arthur; Bang, Kihoon; et al, NANO ENERGY, v.98, 2022-07 |
Path Loss Model Based on Machine Learning Using Multi-Dimensional Gaussian Process Regression Jang, Ki Joung; Park, Sejun; Kim, Junseok; Yoon, Youngkeun; Kim, Chung-Sup; Chong, Young-Jun; Hwang, Ganguk, IEEE ACCESS, v.10, pp.115061 - 115073, 2022 |
Semi-analytic PINN methods for singularly perturbed boundary value problems Gie, Gung-Min; Hong, Youngjoon; Jung, Chang-Yeol, APPLICABLE ANALYSIS, v.103, no.14, pp.2554 - 2571, 2024-09 |
Discover