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cs.LG2026
EIDOS: Latent-Space Predictive Learning for Time Series Foundation Models
Xinxing Zhou, Qingren Yao, Yiji Zhao +5
Most time series foundation models are pretrained by directly predicting future observations, which often yields weakly structured latent representations that capture surface noise…
cs.LG2024★ 1 cited
EffiCANet: Efficient Time Series Forecasting with Convolutional Attention
Xinxing Zhou, Jiaqi Ye, Shubao Zhao +4
The exponential growth of multivariate time series data from sensor networks in domains like industrial monitoring and smart cities requires efficient and accurate forecasting mode…
cs.LG2024
Towards Universal Large-Scale Foundational Model for Natural Gas Demand Forecasting
Xinxing Zhou, Jiaqi Ye, Shubao Zhao +6
In the context of global energy strategy, accurate natural gas demand forecasting is crucial for ensuring efficient resource allocation and operational planning. Traditional foreca…