A framework for baseline load estimation in demand response: Data mining approach. - Saehong Park; Seunghyoung Ryu; Yohwan Choi; Hongseok Kim (SmartGridComm, 2014)

Deep neural network based demand side short term load forecasting. - Seunghyoung Ryu; Jaekoo Noh; Hongseok Kim (SmartGridComm, 2016)

Short-Term Load Forecasting based on ResNet and LSTM. - Hyungeun Choi; Seunghyoung Ryu; Hongseok Kim (SmartGridComm, 2018)

Residential Load Profile Clustering via Deep Convolutional Autoencoder. - Seunghyoung Ryu; Hyungeun Choi; Hyoseop Lee; Hongseok Kim; Vincent W. S. Wong 001 (SmartGridComm, 2018)

Gaussian Residual Bidding Based Coalition for Two-Settlement Renewable Energy Market. - Seunghyoung Ryu; Sunghwan Bae; Jong-Uk Lee; Hongseok Kim (IEEE Access, 2018)

Machine Learning-Based Lithium-Ion Battery Capacity Estimation Exploiting Multi-Channel Charging Profiles. - Yohwan Choi; Seunghyoung Ryu; Kyungnam Park; Hongseok Kim (IEEE Access, 2019)

Denoising Autoencoder-Based Missing Value Imputation for Smart Meters. - Seunghyoung Ryu; Minsoo Kim; Hongseok Kim (IEEE Access, 2020)

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)

Probabilistic deep learning model as a tool for supporting the fast simulation of a thermal-hydraulic code. - Seunghyoung Ryu; Hyeonmin Kim; Seung-Geun Kim; Kyungho Jin; Jaehyun Cho; Jinkyun Park (Expert Syst. Appl., 2022)

An approach to constructing effective training data for a classification model to evaluate the reliability of a passive safety system. - Kyungho Jin; Hyeonmin Kim; Seunghyoung Ryu; Seung-Geun Kim; Jinkyun Park (Reliab. Eng. Syst. Saf., 2022)

Quantile-Mixer: A Novel Deep Learning Approach for Probabilistic Short-Term Load Forecasting. - Seunghyoung Ryu; Yonggyun Yu (IEEE Trans. Smart Grid, 2024)

Can Untrained Neural Networks Detect Anomalies? - Seunghyoung Ryu; Yonggyun Yu; Hogeon Seo (IEEE Trans. Ind. Informatics, 2024)