3 papers
cs.LG2026
SEDformer: Event-Synchronous Spiking Transformers for Irregular Telemetry Time Series Forecasting
Ziyu Zhou, Yuchen Fang, Weilin Ruan +3
Telemetry streams from large-scale Internet-connected systems (e.g., IoT deployments and online platforms) naturally form an irregular multivariate time series (IMTS) whose accurat…
cs.LG2025
Revitalizing Canonical Pre-Alignment for Irregular Multivariate Time Series Forecasting
Ziyu Zhou, Yiming Huang, Yanyun Wang +3
Irregular multivariate time series (IMTS), characterized by uneven sampling and inter-variate asynchrony, fuel many forecasting applications yet remain challenging to model efficie…
cs.LG2025
Multi-Order Wavelet Derivative Transform for Deep Time Series Forecasting
Ziyu Zhou, Jiaxi Hu, Qingsong Wen +2
In deep time series forecasting, the Fourier Transform (FT) is extensively employed for frequency representation learning. However, it often struggles in capturing multi-scale, tim…