方法证据记录
LightTS
LightTS is a lightweight, MLP-based architecture for multivariate time-series forecasting introduced by Tianping Zhang and colleagues in 2022. Motivated by the observation that simpler models can match or surpass heavy Transformer-based architectures, LightTS applies an interval-sampling strategy to decompose long input sequences into multiple sub-sequences and processes each with compact Chunk-MLP and Continuous-MLP modules. The design prioritizes computational efficiency while preserving both local and global temporal patterns.
源记录
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LightTS (Light Sampling-oriented MLP)
分类方法记录 · ml-model / deep-learning
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