Method evidence record
N-HiTS
N-HiTS (Neural Hierarchical Interpolation for Time Series Forecasting), introduced by Challu and colleagues in 2023, is a deep neural forecasting architecture that combines the hierarchical forecasts of multiple stacks operating at different sampling rates and merges them through interpolation. It extends N-BEATS to deliver markedly better accuracy on long forecast horizons.
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Neural Hierarchical Interpolation for Time Series Forecasting
Taxonomic method record · ml-model / deep-learning
- Challu, C. et al. (2023). NHITS: Neural Hierarchical Interpolation for Time Series Forecasting. AAAI. · DOI 10.1609/aaai.v37i6.25854
- Oreshkin, B.N. et al. (2020). N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting. ICLR. arXiv: 1905.10437 · URL
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