Learning Inter-Channel Dependencies for Time-Series Channel Prediction
J. Lee, S. Lee, S. Kim, S. Chae, H. Yu
Addressing Spectral Energy Imbalance in Time-Series Forecasting with Gini-Guided Progressive Frequency Extraction
J. Lee, S. Hong, S. Lee, S. Kim, S. Kang, H. Yu
Dynamic Multi-period Experts for Online Time Series Forecasting, WWW 2026.
S. Hong, S. Chae, S. Kim, S. Jang, H. Yu
Harmonic Dataset Distillation for Time Series Forecasting, AAAI 2026.
S. Hong, S. Jang, W. Kweon, S. Kim, G. Lee, H. Yu
Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark, KDD 2025.
S. Kim, S. Kang, D. Kim, J. Ok, H. Yu
Learning Discriminative Dynamics with Label Corruption for Noisy Label Detection, CVPR 2024.
S. Kim, D. Lee, S. Kang, S. Chae, S. Jang, H. Yu
Eliciting Instruction-tuned Code Language Models’ Capabilities to Utilize Auxiliary Function for Code Generation, EMNLP Findings 2024.
S. Lee, S. Kim, J. Jang, H. Chon, D. Lee, H. Yu
Learning Topology-Specific Experts for Molecular Property Prediction, AAAI 2023.
S. Kim, D. Lee, S. Kang, S. Lee, H. Yu
Learnable Structural Semantic Readout for Graph Classification, ICDM 2021.
D. Lee, S. Kim, S. Lee, C. Park, H. Yu