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Found 3 papers, 2 papers with code
SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
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 dependencies over extended horizons with minimal computational resources.
SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting
To address these issues, we propose two novel strategies to reduce the number of iterations in RNNs for LTSF tasks: Segment-wise Iterations and Parallel Multi-step Forecasting (PMF).
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PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer
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 outperform numerous Transformer-based approaches.
