3 papers
cs.LG2025
PromptTSS: A Prompting-Based Approach for Interactive Multi-Granularity Time Series Segmentation
Ching Chang, Ming-Chih Lo, Wen-Chih Peng +1
Multivariate time series data, collected across various fields such as manufacturing and wearable technology, exhibit states at multiple levels of granularity, from coarse-grained…
cs.LG2024
Text2Freq: Learning Series Patterns from Text via Frequency Domain
Ming-Chih Lo, Ching Chang, Wen-Chih Peng
Traditional time series forecasting models mainly rely on historical numeric values to predict future outcomes.While these models have shown promising results, they often overlook…
cs.LG2024
Self-Supervised Learning of Disentangled Representations for Multivariate Time-Series
Ching Chang, Chiao-Tung Chan, Wei-Yao Wang +2
Multivariate time-series data in fields like healthcare and industry are informative but challenging due to high dimensionality and lack of labels. Recent self-supervised learning…