Conference

119. Seongho Yoon, Jun-Geol Baek, "Efficient Continual Anomaly Detection via Zero-Shot Structural Knowledge Distillation and Prompt Tuning", MLMI 2026: Machine Learning and Machine Intelligence, Tokyo, Japan , 2026.07.

118. Wonhwa Choi, Jun-Geol Baek , "Frequency-Selective Learning under Contaminated Training Data for Vibration Signals ", MLMI 2026: Machine Learning and Machine Intelligence, Tokyo, Japan , 2026.07.

117. Kwanyong Park, Jun-Geol Baek, "Dcausal-TGAN: A Causal Graph-Aware Generative Model for Synthetic Tabular Data ", MLMI 2026: Machine Learning and Machine Intelligence, Tokyo, Japan , 2026.07.

116. Yonggon Jung, Jun-Geol Baek, "Test-Time Adaptive Tabular Transformers via Memory-Aware Gating and Surprise-Driven Learning", ICCRD 2026: 2026 18th International Conference on Computer Research and Development, Singapole, 2026.01.

115. Yongeun Jang, Jun-Geol Baek, "A Gated Attention-Based Semi-Supervised Learning Framework for Robust Representation on Label-Scarce Tabular Data", ICCRD 2026: 2026 18th International Conference on Computer Research and Development, Singapole, 2026.01.

114. Hyebin Suh, Jun-Geol Baek, "DB-CL: Dual-Branch Continual Learning for Time-Series Anomaly Detection under Contextual Concept Drift", ICCRD 2026: 2026 18th International Conference on Computer Research and Development, Singapole, 2026.01.

113. Sangjae Lee, Jun-Geol Baek, "A Data-Driven Framework for Handling Domain Shifts and Unknown Classes in Visual Recognition Systems", ICCRD 2026: 2026 18th International Conference on Computer Research and Development, Singapole, 2026.01.

112. Yoonji Ha, Jun-Geol Baek, "Dynamic Test-Time Adaptation with Masked Autoencoder for Robust Anomaly Detection in Multivariate Time-Series", MLMI 2025: The 8th International Conference on Machine Learning and Machine Intelligence, Kyoto, Japan, 2025.07.

111. Keonhyeok Yoo, Jun-Geol Baek, "Contrastive Learning for Multivariate Time Series Anomaly Detection via Data Degradation", MLMI 2025: The 8th International Conference on Machine Learning and Machine Intelligence, Kyoto, Japan, 2025.07.

110. Jiyul Ham, Jun-Geol Baek, "DHR-CLIP: Dynamic High-Resolution Object-agnostic Prompt Learning for Zero-shot Anomaly Segmentation", ICAIIC 2025: International Conference on Artificial Intelligence in Information and Communication, Fukuoka, Japan, 2025.02.