Woo Youn Kim - RankMe

40 papers A* 5Journal 35

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning Adaptive Perturbation-Conditioned Contexts for Robust Transcriptional Response Prediction. CoRR Yinhua Piao, Hyomin Kim, Seonghwan Kim, Yunhak Oh, Junhyeok Jeon, Sang-Yeon Hwang, Jaechang Lim, Woo Youn Kim, Chanyoung Park, Sungsoo Ahn
2026	J	`jnl`	Progressive Multi-Agent Reasoning for Biological Perturbation Prediction. CoRR Hyomin Kim, Sang-Yeon Hwang, Jaechang Lim, Yinhua Piao, Yunhak Oh, Woo Youn Kim, Chanyoung Park, Sungsoo Ahn, Junhyeok Jeon
2026	J	`jnl`	Riemannian denoising model for molecular structure optimization with chemical accuracy. Nat. Comput. Sci. Jeheon Woo, Seonghwan Kim, Jun Hyeong Kim, Woo Youn Kim
2025	A*	`conf`	Compositional Flows for 3D Molecule and Synthesis Pathway Co-design. ICML Tony Shen, Seonghwan Seo, Ross Irwin, Kieran Didi, Simon Olsson, Woo Youn Kim, Martin Ester
2025	J	`jnl`	Compositional Flows for 3D Molecule and Synthesis Pathway Co-design. CoRR Tony Shen, Seonghwan Seo, Ross Irwin, Kieran Didi, Simon Olsson, Woo Youn Kim, Martin Ester
2025	A*	`conf`	Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation. ICLR Jun Hyeong Kim, Seonghwan Kim, Seokhyun Moon, Hyeongwoo Kim, Jeheon Woo, Woo Youn Kim
2025	A*	`conf`	Generative Flows on Synthetic Pathway for Drug Design. ICLR Seonghwan Seo, Minsu Kim, Tony Shen, Martin Ester, Jinkyoo Park, Sungsoo Ahn, Woo Youn Kim
2025	J	`jnl`	HepatoToxicity Portal (HTP): an integrated database of drug-induced hepatotoxicity knowledgebase and graph neural network-based prediction model. J. Cheminformatics Jiyeon Han, Wonho Zhung, Insoo Jang, Joongwon Lee, Min Ji Kang, Timothy Dain Lee, Seung Jun Kwack, Kyu-Bong Kim, Daehee Hwang, Byungwook Lee, Hyung Sik Kim, Woo Youn Kim, Sanghyuk Lee
2025	J	`jnl`	MetalloGen: Automated 3D Conformer Generation for Diverse Coordination Complexes. J. Chem. Inf. Model. Kyunghoon Lee, Shinyoung Park, Minseong Park, Woo Youn Kim
2025	A*	`conf`	Transition Path Sampling with Improved Off-Policy Training of Diffusion Path Samplers. ICLR Kiyoung Seong, Seonghyun Park, Seonghwan Kim, Woo Youn Kim, Sungsoo Ahn
2024	J	`jnl`	Collective Variable Free Transition Path Sampling with Generative Flow Network. CoRR Kiyoung Seong, Seonghyun Park, Seonghwan Kim, Woo Youn Kim, Sungsoo Ahn
2024	J	`jnl`	DFRscore: Deep Learning-Based Scoring of Synthetic Complexity with Drug-Focused Retrosynthetic Analysis for High-Throughput Virtual Screening. J. Chem. Inf. Model. Hyeongwoo Kim, Kyunghoon Lee, Chansu Kim, Jaechang Lim, Woo Youn Kim
2024	J	`jnl`	Deep Learning-Based Chemical Similarity for Accelerated Organic Light-Emitting Diode Materials Discovery. J. Chem. Inf. Model. Hyeonsu Kim, Kyunghoon Lee, Jun Hyeong Kim, Woo Youn Kim
2024	J	`jnl`	Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation. CoRR Jun Hyeong Kim, Seonghwan Kim, Seokhyun Moon, Hyeongwoo Kim, Jeheon Woo, Woo Youn Kim
2024	J	`jnl`	Generative Flows on Synthetic Pathway for Drug Design. CoRR Seonghwan Seo, Minsu Kim, Tony Shen, Martin Ester, Jinkyoo Park, Sungsoo Ahn, Woo Youn Kim
2024	J	`jnl`	NCIDiff: Non-covalent Interaction-generative Diffusion Model for Improving Reliability of 3D Molecule Generation Inside Protein Pocket. CoRR Joongwon Lee, Wonho Zhung, Woo Youn Kim
2024	J	`jnl`	Riemannian Denoising Score Matching for Molecular Structure Optimization with Accurate Energy. CoRR Jeheon Woo, Seonghwan Kim, Jun Hyeong Kim, Woo Youn Kim
2024	J	`jnl`	TacoGFN: Target-conditioned GFlowNet for Structure-based Drug Design. Trans. Mach. Learn. Res. Tony Shen, Seonghwan Seo, Grayson Lee, Mohit Pandey, Jason R. Smith, Artem Cherkasov, Woo Youn Kim, Martin Ester
2023	J	`jnl`	A 2D Graph-Based Generative Approach For Exploring Transition States Using Diffusion Model. CoRR Seonghwan Kim, Jeheon Woo, Woo Youn Kim
2023	J	`jnl`	C3Net: interatomic potential neural network for prediction of physicochemical properties in heterogenous systems. CoRR Sehan Lee, Jaechang Lim, Woo Youn Kim
2023	A*	`conf`	GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising. NeurIPS Hyeonsu Kim, Jeheon Woo, Seonghwan Kim, Seokhyun Moon, Jun Hyeong Kim, Woo Youn Kim
2023	J	`jnl`	PIGNet2: A Versatile Deep Learning-based Protein-Ligand Interaction Prediction Model for Binding Affinity Scoring and Virtual Screening. CoRR Seokhyun Moon, Sang-Yeon Hwang, Jaechang Lim, Woo Youn Kim
2023	J	`jnl`	PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling. CoRR Seonghwan Seo, Woo Youn Kim
2023	J	`jnl`	Predicting quantum chemical property with easy-to-obtain geometry via positional denoising. CoRR Hyeonsu Kim, Jeheon Woo, Seonghwan Kim, Seokhyun Moon, Jun Hyeong Kim, Woo Youn Kim
2023	J	`jnl`	pyMCD: Python package for searching transition states via the multicoordinate driven method. Comput. Phys. Commun. Kyunghoon Lee, Jun Hyeong Kim, Woo Youn Kim
2021	J	`jnl`	Fragment-based molecular generative model with high generalization ability and synthetic accessibility. CoRR Seonghwan Seo, Jaechang Lim, Woo Youn Kim
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
2020	J	`jnl`	PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictions. CoRR Seokhyun Moon, Wonho Zhung, Soojung Yang, 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`	Scaffold-based molecular design using graph generative model. CoRR Jaechang Lim, Sang-Yeon Hwang, Seungsu Kim, Seokhyun Moon, 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`	Kohn-Sham approach for fast hybrid density functional calculations in real-space numerical grid methods. Comput. Phys. Commun. Jaewook Kim, Sungwoo Kang, Jaechang Lim, Sang-Yeon Hwang, 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
2016	J	`jnl`	Performance of heterogeneous computing with graphics processing unit and many integrated core for hartree potential calculations on a numerical grid. J. Comput. Chem. Sunghwan Choi, Oh-Kyoung Kwon, Jaewook Kim, Woo Youn Kim
2008	J	`jnl`	Carbon nanotube, graphene, nanowire, and molecule-based electron and spin transport phenomena using the nonequilibrium Green's function method at the level of first principles theory. J. Comput. Chem. Woo Youn Kim, Kwang S. Kim