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Yongchan Kwon

Showing results (1-10 of 5) with videos related to

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Chemical Science|December 6, 2019
A Bayesian graph convolutional network for reliable prediction of molecular properties with uncertainty quantificationSeongok Ryu, Yongchan Kwon, Woo Youn Kim
Biometrika|June 10, 2016
Calibrated propensity score method for survey nonresponse in cluster samplingJae Kwang Kim, Yongchan Kwon, Myunghee Cho Paik
Journal of Chemical Information and Modeling|November 9, 2020
Comprehensive Study on Molecular Supervised Learning with Graph Neural NetworksDoyeong Hwang, Soojung Yang, Yongchan Kwon, et al.
Frontiers in Neurology|October 2, 2018
ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRIStefan Winzeck, Arsany Hakim, Richard McKinley, et al.
Nature Communications|August 30, 2022
Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategyVictoria N Parikh, Alexander G Ioannidis, David Jimenez-Morales, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
Chemical Science|December 6, 2019
A Bayesian graph convolutional network for reliable prediction of molecular properties with uncertainty quantificationSeongok Ryu, Yongchan Kwon, Woo Youn Kim
Biometrika|June 10, 2016
Calibrated propensity score method for survey nonresponse in cluster samplingJae Kwang Kim, Yongchan Kwon, Myunghee Cho Paik
Journal of Chemical Information and Modeling|November 9, 2020
Comprehensive Study on Molecular Supervised Learning with Graph Neural NetworksDoyeong Hwang, Soojung Yang, Yongchan Kwon, et al.
Frontiers in Neurology|October 2, 2018
ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRIStefan Winzeck, Arsany Hakim, Richard McKinley, et al.
Nature Communications|August 30, 2022
Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategyVictoria N Parikh, Alexander G Ioannidis, David Jimenez-Morales, et al.
Pageof 1