4 papers
Unsupervised Time Series Anomaly Prediction with Importance-based Generative Contrastive Learning
Kai Zhao, Zhihao Zhuang, Chenjuan Guo +3
Time series anomaly prediction plays an essential role in many real-world scenarios, such as environmental prevention and prompt maintenance of cyber-physical systems. However, exi…
CC-Time: Cross-Model and Cross-Modality Time Series Forecasting
Peng Chen, Yihang Wang, Yang Shu +6
With the success of pre-trained language models (PLMs) in various application fields beyond natural language processing, language models have raised emerging attention in the field…
AimTS: Augmented Series and Image Contrastive Learning for Time Series Classification
Yuxuan Chen, Shanshan Huang, Yunyao Cheng +6
Time series classification (TSC) is an important task in time series analysis. Existing TSC methods mainly train on each single domain separately, suffering from a degradation in a…
Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting
Peng Chen, Yingying Zhang, Yunyao Cheng +5
Transformers for time series forecasting mainly model time series from limited or fixed scales, making it challenging to capture different characteristics spanning various scales.…