5 papers · 1 filter
Efficient Test-Time Scaling for LLM-based Time Series Forecasting
Xuan-May Le, Minh-Tuan Tran, Ling Luo +3
Long-term time series forecasting benefits from preserving global structure such as trends and seasonality. Recent LLM-based forecasters often improve accuracy through test-time sc…
Softmax is not Enough (for Adaptive Conformal Classification)
Navid Akhavan Attar, Hesam Asadollahzadeh, Ling Luo +1
The merit of Conformal Prediction (CP), as a distribution-free framework for uncertainty quantification, depends on generating prediction sets that are efficient, reflected in smal…
Dynamical Label Augmentation and Calibration for Noisy Electronic Health Records
Yuhao Li, Ling Luo, Uwe Aickelin
Medical research, particularly in predicting patient outcomes, heavily relies on medical time series data extracted from Electronic Health Records (EHR), which provide extensive in…
SHIP: A Shapelet-based Approach for Interpretable Patient-Ventilator Asynchrony Detection
Xuan-May Le, Ling Luo, Uwe Aickelin +3
Patient-ventilator asynchrony (PVA) is a common and critical issue during mechanical ventilation, affecting up to 85% of patients. PVA can result in clinical complications such as…
ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification
Xuan-May Le, Ling Luo, Uwe Aickelin +1
Multivariate time series classification (MTSC) has attracted significant research attention due to its diverse real-world applications. Recently, exploiting transformers for MTSC h…