4 papers
A Unified Shape-Aware Foundation Model for Time Series Classification
Zhen Liu, Yucheng Wang, Boyuan Li +4
Foundation models pre-trained on large-scale source datasets are reshaping the traditional training paradigm for time series classification. However, existing time series foundatio…
Learning Soft Sparse Shapes for Efficient Time-Series Classification
Zhen Liu, Yicheng Luo, Boyuan Li +3
Shapelets are discriminative subsequences (or shapes) with high interpretability in time series classification. Due to the time-intensive nature of shapelet discovery, existing sha…
HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting
Boyuan Li, Yicheng Luo, Zhen Liu +3
Irregular multivariate time series (IMTS) are characterized by irregular time intervals within variables and unaligned observations across variables, posing challenges in learning…
Meta-Stock: Task-Difficulty-Adaptive Meta-learning for Sub-new Stock Price Prediction
Linghao Wang, Zhen Liu, Peitian Ma +1
Sub-new stock price prediction, forecasting the price trends of stocks listed less than one year, is crucial for effective quantitative trading. While deep learning methods have de…