5 papers · 1 filter
Domain Generalization under Sampling Pattern Shifts in Irregular Time Series
Changhun Kim, Joohyung Lee, Kwanhyung Lee +3
Irregularly sampled multivariate time series (ISMTS) are prevalent in real-world applications, where both observation times and available measurements can vary substantially across…
ChronoFlow: Hierarchical Flow Matching for Irregular Time Series Generation
Changhun Kim, Sunguk Jang, Jeongjun Lee +5
Recent advances in generative modeling have substantially improved time series generation, yet most existing methods either assume a regular temporal grid or focus on feature dynam…
TRIAGE: Dialectical LLM Reasoning for Explainable Risk Prediction on Irregularly Sampled Medical Time Series
Hyeongwon Jang, Gyouk Chu, Changhun Kim +4
Clinical early warning systems built on irregularly sampled medical time series (ISMTS) from electronic health records must deliver continuous risk scores for patient triage as wel…
Structure-Aware Set Transformers: Temporal and Variable-Type Attention Biases for Asynchronous Clinical Time Series
Joohyung Lee, Kwanhyung Lee, Changhun Kim +1
Electronic health records (EHR) are irregular, asynchronous multivariate time series. As time-series foundation models increasingly tokenize events rather than discretizing time, t…
Soft Equivariance Regularization for Invariant Self-Supervised Learning
Joohyung Lee, Changhun Kim, Hyunsu Kim +2
Self-supervised learning (SSL) typically learns representations invariant to semantic-preserving augmentations. While effective for recognition, enforcing strong invariance can sup…