Browse "Dept. of Chemistry(화학과)" by Author Ryu, Seongok
Showing results 1 to 14 of 14
A Bayesian graph convolutional network for reliable prediction of molecular properties with uncertainty quantification Ryu, Seongok; Kwon, Yongchan; Kim, Woo Youn, CHEMICAL SCIENCE, v.10, no.36, pp.8438 - 8446, 2019-09 |
| Bayesian's eye on molecular science: Bayesian deep optimization of Onsager-Machlup action learning for uncertainty quantification and active learning of molecular properties Ryu, Seongok; Kwon, Yongchan; Hwang, Sang-Yeon; Kim, Woo Youn, The 5 th International Conference on Molecular Simulation, The Korean Institute of Metals and Materials, The Korea Institute of Science and Technology, Korea Advanced Institute of Science and Technology - ACE Team, Seoul National University, 2019-11-04 |
| Development of machine learning systems for drug discovery = 신약개발을 위한 머신러닝 시스템의 개발link Ryu, Seongok; Kim, Woo Youn; et al, 한국과학기술원, 2020 |
| Effects of the locality of a potential derived from hybrid density functionals on Kohn-Sham orbitals and excited states Kim, Jaewook; Hong, Kwang-Woo; Hwang, Sang-Yeon; Ryu, Seongok; Choi, Sunghwan; Kim, Woo Youn, PHYSICAL CHEMISTRY CHEMICAL PHYSICS, v.19, no.15, pp.10177 - 10186, 2017-04 |
| Importance of local exact exchange potential in hybrid functionals for accurate excited states Kim, Jaewook; Hong, Kwang-Woo; Sungwoo, Kang; LIM, JAE; Hwang, Sang-Yeon; Ryu, Seongok; Choi, Sunghwan; et al, 11th Triennial Congress of the World Association of Theoretical and Computational Chemists, Ludwig-Maximilians-Universität (LMU), 2017-08-29 |
| Molecular Generative Model Based on an Adversarially Regularized Autoencoder Hong, Seung Hwan; Ryu, Seongok; Lim, Jaechang; Kim, Woo Youn, JOURNAL OF CHEMICAL INFORMATION AND MODELING, v.60, no.1, pp.29 - 36, 2020-01 |
| Molecular generative model based on conditional variational autoencoder for de novo molecular design Lim, Jaechang; Ryu, Seongok; Kim, Jin Woo; Kim, Woo Youn, JOURNAL OF CHEMINFORMATICS, v.10, 2018-07 |
| Performance of Range-Separated Hybrid Functional with Krieger-Li-Iafrate Potential for Molecular Excitation Energies Sungwoo, Kang; Kim, Jaewook; Choi, Sunghwan; LIM, JAE; Hwang, Sang-Yeon; Ryu, Seongok; Kim, Woo Youn, 11th Triennial Congress of the World Association of Theoretical and Computational Chemists, Ludwig-Maximilians-Universität (LMU), 2017-08-29 |
| Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks Lim, Jaechang; Ryu, Seongok; Park, Kyubyong; Choe, Yo Joong; Ham, Jiyeon; Kim, Woo Youn, The 5 th International Conference on Molecular Simulation, The Korean Institute of Metals and Materials, The Korea Institute of Science and Technology, Korea Advanced Institute of Science and Technology - ACE Team, Seoul National University, 2019-11-05 |
| Predicting Drug-Target Interaction Using a Novel Graph Neural Network with 3D Structure-Embedded Graph Representation Lim, Jaechang; Ryu, Seongok; Park, Kyubyong; Choe, Yo Joong; Ham, Jiyeon; Kim, Woo Youn, JOURNAL OF CHEMICAL INFORMATION AND MODELING, v.59, no.9, pp.3981 - 3988, 2019-09 |
| Supersampling double grid method to improve accuracy of real space electronic structure calculation Ryu, Seongok; Choi, Sunghwan; Hong, Kwang-Woo; Kim, Woo-Youn, IUPAC-2015, Korean Chemical Society, 2015-08-13 |
| Supersampling method for efficient grid-based electronic structure calculations Ryu, Seongok; Choi, Sunghwan; Hong, Kwangwoo; Kim, Woo Youn, JOURNAL OF CHEMICAL PHYSICS, v.144, no.9, 2016-03 |
| Uncertainty quantification of molecule property predictions using Bayesian neural network models Ryu, Seongok; Kwon, Yongchan; Kim, Woo Youn, Workshop on "Machine Learning for Molecules and Materials", 32nd Neural Information Processing Systems, NeurIPS Foundation, 2018-12-08 |
| Update to ACE-molecule: Projector augmented wave method on lagrange-sinc basis set Kang, Sungwoo; Ryu, Seongok; Choi, Sunghwan; Kim, Jaewook; Hong, Kwangwoo; Kim, Woo Youn, INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, v.116, no.8, pp.644 - 650, 2016-04 |
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