5 papers
Energy-Aware Pattern Disentanglement: A Generalizable Pattern Assisted Architecture for Multi-task Time Series Analysis
Xiangkai Ma, Xiaobin Hong, Wenzhong Li +1
Time series analysis has found widespread applications in areas such as weather forecasting, anomaly detection, and healthcare. While deep learning approaches have achieved signifi…
Semantic-Supervised Spatial-Temporal Fusion for LiDAR-based 3D Object Detection
Chaoqun Wang, Xiaobin Hong, Wenzhong Li +1
LiDAR-based 3D object detection presents significant challenges due to the inherent sparsity of LiDAR points. A common solution involves long-term temporal LiDAR data to densify th…
Unify and Anchor: A Context-Aware Transformer for Cross-Domain Time Series Forecasting
Xiaobin Hong, Jiawen Zhang, Wenzhong Li +2
The rise of foundation models has revolutionized natural language processing and computer vision, yet their best practices to time series forecasting remains underexplored. Existin…
Domain Fusion Controllable Generalization for Cross-Domain Time Series Forecasting from Multi-Domain Integrated Distribution
Xiangkai Ma, Xiaobin Hong, Mingkai Lin +3
Conventional deep models have achieved unprecedented success in time series forecasting. However, facing the challenge of cross-domain generalization, existing studies utilize stat…
A Wave is Worth 100 Words: Investigating Cross-Domain Transferability in Time Series
Xiangkai Ma, Xiaobin Hong, Wenzhong Li +1
Time series analysis is a fundamental data mining task that supervised training methods based on empirical risk minimization have proven their effectiveness on specific tasks and d…