Yonggyun Yu

According to our database, Yonggyun Yu authored at least 7 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of six.
• Erdős number of five.

2024

Can Untrained Neural Networks Detect Anomalies?

Seunghyoung Ryu, Yonggyun Yu, Hogeon Seo

IEEE Trans. Ind. Informatics, April, 2024

Quantile-Mixer: A Novel Deep Learning Approach for Probabilistic Short-Term Load Forecasting.

Seunghyoung Ryu, Yonggyun Yu

IEEE Trans. Smart Grid, 2024

Dynamic graph-based convergence acceleration for topology optimization in unstructured meshes.

Younghwan Joo, Heesun Choi, Gil-Eon Jeong, Yonggyun Yu

Eng. Appl. Artif. Intell., 2024

Reinforcement Learning-Based Delay Line Design for Crosstalk Minimization.

Jaeho Jung, Yonggyun Yu, Soobum Lee

IEEE Access, 2024

2022

Quantile Autoencoder With Abnormality Accumulation for Anomaly Detection of Multivariate Sensor Data.

Seunghyoung Ryu, Jiyeon Yim, Junghoon Seo, Yonggyun Yu, Hogeon Seo

IEEE Access, 2022

2021

Unit Module-Based Convergence Acceleration for Topology Optimization Using the Spatiotemporal Deep Neural Network.

Younghwan Joo, Yonggyun Yu, In Gwun Jang

IEEE Access, 2021

2018

Deep learning for topology optimization design.

Yonggyun Yu, Taeil Hur, Jaeho Jung

CoRR, 2018