Woo Youn Kim

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 25

Top Topics

Dempster Shafer

Graph Representation

Top Venues

J. Chem. Inf. Model.

Comput. Phys. Commun.

J. Comput. Chem.

Publications

Joongwon Lee, Wonho Zhung, Woo Youn Kim
NCIDiff: Non-covalent Interaction-generative Diffusion Model for Improving Reliability of 3D Molecule Generation Inside Protein Pocket. CoRR (2024)
Hyeongwoo Kim, Kyunghoon Lee, Chansu Kim, Jaechang Lim, Woo Youn Kim
DFRscore: Deep Learning-Based Scoring of Synthetic Complexity with Drug-Focused Retrosynthetic Analysis for High-Throughput Virtual Screening. J. Chem. Inf. Model. 64 (7) (2024)
Hyeonsu Kim, Kyunghoon Lee, Jun Hyeong Kim, Woo Youn Kim
Deep Learning-Based Chemical Similarity for Accelerated Organic Light-Emitting Diode Materials Discovery. J. Chem. Inf. Model. 64 (3) (2024)
Kiyoung Seong, Seonghyun Park, Seonghwan Kim, Woo Youn Kim, Sungsoo Ahn
Collective Variable Free Transition Path Sampling with Generative Flow Network. CoRR (2024)
Hyeonsu Kim, Jeheon Woo, Seonghwan Kim, Seokhyun Moon, Jun Hyeong Kim, Woo Youn Kim
GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising. NeurIPS (2023)
Sehan Lee, Jaechang Lim, Woo Youn Kim
C3Net: interatomic potential neural network for prediction of physicochemical properties in heterogenous systems. CoRR (2023)
Hyeonsu Kim, Jeheon Woo, Seonghwan Kim, Seokhyun Moon, Jun Hyeong Kim, Woo Youn Kim
Predicting quantum chemical property with easy-to-obtain geometry via positional denoising. CoRR (2023)
Kyunghoon Lee, Jun Hyeong Kim, Woo Youn Kim
pyMCD: Python package for searching transition states via the multicoordinate driven method. Comput. Phys. Commun. 291 (2023)
Seonghwan Seo, Woo Youn Kim
PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling. CoRR (2023)
Seonghwan Kim, Jeheon Woo, Woo Youn Kim
A 2D Graph-Based Generative Approach For Exploring Transition States Using Diffusion Model. CoRR (2023)
Seokhyun Moon, Sang-Yeon Hwang, Jaechang Lim, Woo Youn Kim
PIGNet2: A Versatile Deep Learning-based Protein-Ligand Interaction Prediction Model for Binding Affinity Scoring and Virtual Screening. CoRR (2023)
Seonghwan Seo, Jaechang Lim, Woo Youn Kim
Fragment-based molecular generative model with high generalization ability and synthetic accessibility. CoRR (2021)
Seokhyun Moon, Wonho Zhung, Soojung Yang, Jaechang Lim, Woo Youn Kim
PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictions. CoRR (2020)
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)
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)
Jaechang Lim, Sang-Yeon Hwang, Seungsu Kim, Seokhyun Moon, Woo Youn Kim
Scaffold-based molecular design using graph generative model. 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)
Jaewook Kim, Sungwoo Kang, Jaechang Lim, Sang-Yeon Hwang, Woo Youn Kim
Kohn-Sham approach for fast hybrid density functional calculations in real-space numerical grid methods. Comput. Phys. Commun. 230 (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)
Sunghwan Choi, Oh-Kyoung Kwon, Jaewook Kim, Woo Youn Kim
Performance of heterogeneous computing with graphics processing unit and many integrated core for hartree potential calculations on a numerical grid. J. Comput. Chem. 37 (24) (2016)
Woo Youn Kim, Kwang S. Kim
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. 29 (7) (2008)