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2020 – today
- 2024
[j6]Gyoung S. Na
, Hyun Woo Kim:
Metaheuristics-guided active learning for optimizing reaction conditions of high-performance methane conversion. Appl. Soft Comput. 164: 111935 (2024)- 2023
- [c7]Namkyeong Lee, Dongmin Hyun, Gyoung S. Na, Sungwon Kim, Junseok Lee, Chanyoung Park:
Conditional Graph Information Bottleneck for Molecular Relational Learning. ICML 2023: 18852-18871 - [c6]Namkyeong Lee, Kanghoon Yoon, Gyoung S. Na, Sein Kim, Chanyoung Park:
Shift-Robust Molecular Relational Learning with Causal Substructure. KDD 2023: 1200-1212 - [c5]Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun, Gyoung S. Na, Chanyoung Park:
Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer. NeurIPS 2023 - [i5]Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun, Gyoung S. Na, Chanyoung Park:
Predicting Density of States via Multi-modal Transformer. CoRR abs/2303.07000 (2023) - [i4]Namkyeong Lee, Dongmin Hyun, Gyoung S. Na, Sungwon Kim, Junseok Lee, Chanyoung Park:
Conditional Graph Information Bottleneck for Molecular Relational Learning. CoRR abs/2305.01520 (2023) - [i3]Namkyeong Lee, Kanghoon Yoon, Gyoung S. Na, Sein Kim, Chanyoung Park:
Shift-Robust Molecular Relational Learning with Causal Substructure. CoRR abs/2305.18451 (2023) - [i2]Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun, Gyoung S. Na, Chanyoung Park:
Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer. CoRR abs/2311.12856 (2023) - [i1]Namkyeong Lee, Heewoong Noh, Gyoung S. Na, Tianfan Fu, Jimeng Sun, Chanyoung Park:
Stoichiometry Representation Learning with Polymorphic Crystal Structures. CoRR abs/2312.13289 (2023) - 2022
- [j5]Gyoung S. Na:
Eigen-guided deep metric learning. Expert Syst. Appl. 203: 117367 (2022) - [j4]Gyoung S. Na:
Efficient learning rate adaptation based on hierarchical optimization approach. Neural Networks 150: 326-335 (2022) - [j3]Gyoung S. Na, Hyunju Chang:
Unsupervised Subspace Extraction via Deep Kernelized Clustering. ACM Trans. Knowl. Discov. Data 16(1): 20:1-20:15 (2022) - [c4]Gyoung S. Na:
Conditional Graph Regression for Complex Chemical Systems with Heterogeneous Substructures. IEEE Big Data 2022: 1651-1660 - [c3]Gyoung S. Na, Chanyoung Park:
Nonlinearity Encoding for Extrapolation of Neural Networks. KDD 2022: 1284-1294 - 2021
- [j2]Gyoung S. Na, Hyun Woo Kim:
Reverse graph self-attention for target-directed atomic importance estimation. Neural Networks 133: 1-10 (2021) - 2020
- [j1]Gyoung S. Na, Hyun Woo Kim, Hyunju Chang:
Costless Performance Improvement in Machine Learning for Graph-Based Molecular Analysis. J. Chem. Inf. Model. 60(3): 1137-1145 (2020) - [c2]Gyoung S. Na, Hyun Woo Kim, Hyunju Chang:
Scale-Aware Graph-Based Machine Learning for Accurate Molecular Property Prediction. IEEE BigData 2020: 196-203
2010 – 2019
- 2018
- [c1]Gyoung S. Na, Donghyun Kim, Hwanjo Yu:
DILOF: Effective and Memory Efficient Local Outlier Detection in Data Streams. KDD 2018: 1993-2002
Coauthor Index
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