42 citations · 63 across the 5 of their papers we have counts for
5 papers
Temporal Query Network for Efficient Multivariate Time Series Forecasting
Shengsheng Lin, Haojun Chen, Haijie Wu +2
Sufficiently modeling the correlations among variables (aka channels) is crucial for achieving accurate multivariate time series forecasting (MTSF). In this paper, we propose a nov…
CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns
Shengsheng Lin, Weiwei Lin, Xinyi Hu +3
The stable periodic patterns present in time series data serve as the foundation for conducting long-horizon forecasts. In this paper, we pioneer the exploration of explicitly mode…
SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
Shengsheng Lin, Weiwei Lin, Wentai Wu +2
This paper introduces SparseTSF, a novel, extremely lightweight model for Long-term Time Series Forecasting (LTSF), designed to address the challenges of modeling complex temporal…
SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting
Shengsheng Lin, Weiwei Lin, Wentai Wu +3
RNN-based methods have faced challenges in the Long-term Time Series Forecasting (LTSF) domain when dealing with excessively long look-back windows and forecast horizons. Consequen…
PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer
Shengsheng Lin, Weiwei Lin, Wentai Wu +2
Recently, the superiority of Transformer for long-term time series forecasting (LTSF) tasks has been challenged, particularly since recent work has shown that simple models can out…