4 papers
GatedLinear: Adaptive Routing of Complementary Linear Bases for Time Series Forecasting
Qitai Tan, Ruiwen Gu, Yilin Su +3
Time series forecasting requires models to capture diverse, often mutually exclusive, temporal dynamics, from smooth trend continuation to nonstationary drift and strict phase-alig…
PHGNet: Prototype-Guided Hypergraph Construction for Heterogeneous Spatiotemporal Forecasting
Ruiwen Gu, Yahao Liu, Zhenyu Liu +2
As a core task in intelligent transportation systems, traffic forecasting plays a critical role in urban traffic management. Accurate traffic forecasting relies on modeling complex…
ADMFormer: An Adaptive-Decomposition Transformer with Time-Varying Masked Spatial Attention for Traffic Forecasting
Ruiwen Gu, Qitai Tan, Yahao Liu +1
Accurate traffic forecasting is essential for intelligent transportation systems, supporting a wide range of real-world applications. However, it remains challenging due to two key…
SynTSBench: Rethinking Temporal Pattern Learning in Deep Learning Models for Time Series
Qitai Tan, Yiyun Chen, Mo Li +3
Recent advances in deep learning have driven rapid progress in time series forecasting, yet many state-of-the-art models continue to struggle with robust performance in real-world…