Seongok Ryu - RankMe

18 papers A* 1Journal 17

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	SHARP: Generating Synthesizable Molecules via Fragment-Based Hierarchical Action-Space Reinforcement Learning for Pareto Optimization. J. Chem. Inf. Model. Jeonghyeon Kim, Seongok Ryu, Woohyeong Lee, Ansoo Lee, Hahnbeom Park, Chaok Seok
2024	J	`jnl`	CSearch: chemical space search via virtual synthesis and global optimization. J. Cheminformatics Hakjean Kim, Seongok Ryu, Nuri Jung, Jinsol Yang, Chaok Seok
2024	J	`jnl`	Understanding active learning of molecular docking and its applications. CoRR Jeonghyeon Kim, Juno Nam, Seongok Ryu
2022	J	`jnl`	Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning. CoRR Seongok Ryu, Sumin Lee
2021	A*	`conf`	Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation. NeurIPS Soojung Yang, Doyeong Hwang, Seul Lee, Seongok Ryu, Sung Ju Hwang
2021	J	`jnl`	Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation. CoRR Soojung Yang, Doyeong Hwang, Seul Lee, Seongok Ryu, Sung Ju Hwang
2020	J	`jnl`	A benchmark study on reliable molecular supervised learning via Bayesian learning. CoRR Doyeong Hwang, Grace Lee, Hanseok Jo, Seyoul Yoon, Seongok Ryu
2020	J	`jnl`	A comprehensive study on the prediction reliability of graph neural networks for virtual screening. CoRR Soojung Yang, Kyung-Hoon Lee, Seongok Ryu
2020	J	`jnl`	Comprehensive Study on Molecular Supervised Learning with Graph Neural Networks. J. Chem. Inf. Model. Doyeong Hwang, Soojung Yang, Yongchan Kwon, Kyung-Hoon Lee, Grace Lee, Hanseok Jo, Seyeol Yoon, Seongok Ryu
2020	J	`jnl`	Molecular Generative Model Based on an Adversarially Regularized Autoencoder. J. Chem. Inf. Model. Seung Hwan Hong, Seongok Ryu, Jaechang Lim, Woo Youn Kim
2019	J	`jnl`	Molecular Generative Model Based On Adversarially Regularized Autoencoder. CoRR Seung Hwan Hong, Jaechang Lim, Seongok Ryu, Woo Youn Kim
2019	J	`jnl`	Predicting Drug-Target Interaction Using a Novel Graph Neural Network with 3D Structure-Embedded Graph Representation. J. Chem. Inf. Model. Jaechang Lim, Seongok Ryu, Kyubyong Park, Yo Joong Choe, Jiyeon Ham, Woo Youn Kim
2019	J	`jnl`	Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks. CoRR Jaechang Lim, Seongok Ryu, Kyubyong Park, Yo Joong Choe, Jiyeon Ham, Woo Youn Kim
2019	J	`jnl`	Uncertainty quantification of molecular property prediction using Bayesian neural network models. CoRR Seongok Ryu, Yongchan Kwon, Woo Youn Kim
2019	J	`jnl`	Uncertainty quantification of molecular property prediction with Bayesian neural networks. CoRR Seongok Ryu, Yongchan Kwon, Woo Youn Kim
2018	J	`jnl`	Deeply learning molecular structure-property relationships using graph attention neural network. CoRR Seongok Ryu, Jaechang Lim, Woo Youn Kim
2018	J	`jnl`	Molecular generative model based on conditional variational autoencoder for de novo molecular design. CoRR Jaechang Lim, Seongok Ryu, Jin Woo Kim, Woo Youn Kim
2018	J	`jnl`	Molecular generative model based on conditional variational autoencoder for de novo molecular design. J. Cheminformatics Jaechang Lim, Seongok Ryu, Jin Woo Kim, Woo Youn Kim