Gyoung S. Na

According to our database, Gyoung S. Na authored at least 14 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Stoichiometry Representation Learning with Polymorphic Crystal Structures.

Namkyeong Lee, Heewoong Noh, Gyoung S. Na, Tianfan Fu, Jimeng Sun, Chanyoung Park

CoRR, 2023

Predicting Density of States via Multi-modal Transformer.

Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun, Gyoung S. Na, Chanyoung Park

CoRR, 2023

Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer.

Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun, Gyoung S. Na, Chanyoung Park

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Shift-Robust Molecular Relational Learning with Causal Substructure.

Namkyeong Lee, Kanghoon Yoon, Gyoung S. Na, Sein Kim, Chanyoung Park

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Conditional Graph Information Bottleneck for Molecular Relational Learning.

Namkyeong Lee, Dongmin Hyun, Gyoung S. Na, Sungwon Kim, Junseok Lee, Chanyoung Park

Proceedings of the International Conference on Machine Learning, 2023

2022

Eigen-guided deep metric learning.

Gyoung S. Na

Expert Syst. Appl., October, 2022

Unsupervised Subspace Extraction via Deep Kernelized Clustering.

Gyoung S. Na, Hyunju Chang

ACM Trans. Knowl. Discov. Data, 2022

Efficient learning rate adaptation based on hierarchical optimization approach.

Gyoung S. Na

Neural Networks, 2022

Nonlinearity Encoding for Extrapolation of Neural Networks.

Gyoung S. Na, Chanyoung Park

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Conditional Graph Regression for Complex Chemical Systems with Heterogeneous Substructures.

Gyoung S. Na

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Reverse graph self-attention for target-directed atomic importance estimation.

Gyoung S. Na, Hyun Woo Kim

Neural Networks, 2021

2020

Costless Performance Improvement in Machine Learning for Graph-Based Molecular Analysis.

Gyoung S. Na, Hyun Woo Kim, Hyunju Chang

J. Chem. Inf. Model., 2020

Scale-Aware Graph-Based Machine Learning for Accurate Molecular Property Prediction.

Gyoung S. Na, Hyun Woo Kim, Hyunju Chang

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2018

DILOF: Effective and Memory Efficient Local Outlier Detection in Data Streams.

Gyoung S. Na, Donghyun Kim, Hwanjo Yu

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018