Seongok Ryu

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 16

Top Topics

Bayesian Learning

Graph Representation

Molecular Structure

Top Venues

J. Chem. Inf. Model.

J. Cheminformatics

Publications

Jeonghyeon Kim, Juno Nam, Seongok Ryu
Understanding active learning of molecular docking and its applications. CoRR (2024)
Seongok Ryu, Sumin Lee
Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning. CoRR (2022)
Soojung Yang, Doyeong Hwang, Seul Lee, Seongok Ryu, Sung Ju Hwang
Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation. CoRR (2021)
Soojung Yang, Doyeong Hwang, Seul Lee, Seongok Ryu, Sung Ju Hwang
Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation. NeurIPS (2021)
Seung Hwan Hong, Seongok Ryu, Jaechang Lim, Woo Youn Kim
Molecular Generative Model Based on an Adversarially Regularized Autoencoder. J. Chem. Inf. Model. 60 (1) (2020)
Doyeong Hwang, Grace Lee, Hanseok Jo, Seyoul Yoon, Seongok Ryu
A benchmark study on reliable molecular supervised learning via Bayesian learning. CoRR (2020)
Doyeong Hwang, Soojung Yang, Yongchan Kwon, Kyung-Hoon Lee, Grace Lee, Hanseok Jo, Seyeol Yoon, Seongok Ryu
Comprehensive Study on Molecular Supervised Learning with Graph Neural Networks. J. Chem. Inf. Model. 60 (12) (2020)
Soojung Yang, Kyung-Hoon Lee, Seongok Ryu
A comprehensive study on the prediction reliability of graph neural networks for virtual screening. CoRR (2020)
Jaechang Lim, Seongok Ryu, Kyubyong Park, Yo Joong Choe, Jiyeon Ham, Woo Youn Kim
Predicting Drug-Target Interaction Using a Novel Graph Neural Network with 3D Structure-Embedded Graph Representation. J. Chem. Inf. Model. 59 (9) (2019)
Seongok Ryu, Yongchan Kwon, Woo Youn Kim
Uncertainty quantification of molecular property prediction using Bayesian neural network models. CoRR (2019)
Seongok Ryu, Yongchan Kwon, Woo Youn Kim
Uncertainty quantification of molecular property prediction with Bayesian neural networks. CoRR (2019)
Jaechang Lim, Seongok Ryu, Kyubyong Park, Yo Joong Choe, Jiyeon Ham, Woo Youn Kim
Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks. CoRR (2019)
Seung Hwan Hong, Jaechang Lim, Seongok Ryu, Woo Youn Kim
Molecular Generative Model Based On Adversarially Regularized Autoencoder. CoRR (2019)
Jaechang Lim, Seongok Ryu, Jin Woo Kim, Woo Youn Kim
Molecular generative model based on conditional variational autoencoder for de novo molecular design. J. Cheminformatics 10 (1) (2018)
Seongok Ryu, Jaechang Lim, Woo Youn Kim
Deeply learning molecular structure-property relationships using graph attention neural network. CoRR (2018)
Jaechang Lim, Seongok Ryu, Jin Woo Kim, Woo Youn Kim
Molecular generative model based on conditional variational autoencoder for de novo molecular design. CoRR (2018)