89 citations · 89 across the 4 of their papers we have counts for
4 papers
PaP-NF: Probabilistic Long-Term Time Series Forecasting via Prefix-as-Prompt Reprogramming and Normalizing Flows
Minju Kim, Youngbum Hur
Time series forecasting plays a central role in many real-world applications and has been extensively studied. Most existing approaches rely on deterministic models. However, real-…
CALAD: Channel-Aware contrastive Learning for multivariate time series Anomaly Detection
Jaehyeop Hong, Youngbum Hur
Multivariate time series anomaly detection has become increasingly important in real-world applications, where labeled data are often scarce. Many existing approaches rely on unsup…
CoReVAD: A Contextual Reasoning Framework for Training-Free Video Anomaly Detection
Hyeongmuk Lim, Youngbum Hur
Existing Video Anomaly Detection (VAD) methods typically rely on task-specific training, leading to strong domain dependency and high training costs. Moreover, most existing method…
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning
Jaehyung Kim, Youngbum Hur, Sejun Park +3
While semi-supervised learning (SSL) has proven to be a promising way for leveraging unlabeled data when labeled data is scarce, the existing SSL algorithms typically assume that t…