12 papers
SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement
Xiangfei Qiu, Xvyuan Liu, Tianen Shen +4
Time series forecasting is important in many fields that require accurate predictions for decision-making. Patching techniques, commonly used and effective in time series modeling,…
Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting
Xiangfei Qiu, Kangjia Yan, Xvyuan Liu +2
Irregular multivariate time series forecasting (IMTSF) is challenging due to non-uniform sampling and variable asynchronicity. These irregularities violate the equidistant assumpti…
TimeART: Towards Agentic Time Series Reasoning via Tool-Augmentation
Xingjian Wu, Junkai Lu, Zhengyu Li +5
Time series data widely exist in real-world cyber-physical systems. Though analyzing and interpreting them contributes to significant values, e.g, disaster prediction and financial…
DBLoss: Decomposition-based Loss Function for Time Series Forecasting
Xiangfei Qiu, Xingjian Wu, Hanyin Cheng +4
Time series forecasting holds significant value in various domains such as economics, traffic, energy, and AIOps, as accurate predictions facilitate informed decision-making. Howev…
Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective
Xingjian Wu, Xiangfei Qiu, Hanyin Cheng +4
Time Series Forecasting has made significant progress with the help of Patching technique, which partitions time series into multiple patches to effectively retain contextual seman…
Task-Aware Mixture-of-Experts for Time Series Analysis
Xingjian Wu, Zhengyu Li, Hanyin Cheng +4
Time Series Analysis is widely used in various real-world applications such as weather forecasting, financial fraud detection, imputation for missing data in IoT systems, and class…