3 papers
cs.LG2026
Adaptive Oscillatory-State Alignment for Time Series Forecasting
Zhangyao Song, Chaofeng Qu, Chao Zha +3
Long-term time series forecasting benefits from inductive biases that expose recurring temporal structure. Existing periodic forecasting methods typically model recurrence through…
eess.SP2026
ChannelKAN: Multi-Scale Dual-Domain Channel Prediction via Hybrid CNN-KAN Architecture
Nanqing Jiang, Zhangyao Song, Tao Guo +2
Accurate channel state information (CSI) prediction is essential for improving the reliability and spectral efficiency of massive MIMO-OFDM systems in high-mobility scenarios. Exis…
cs.CE2026
Channel, Trend and Periodic-Wise Representation Learning for Multivariate Long-term Time Series Forecasting
Zhangyao Song, Nanqing Jiang, Miaohong He +2
Downsampling-based methods for time series forecasting have attracted increasing attention due to their superiority in capturing sequence trends. However, this approaches mainly ca…