Tabular foundation models applied to PHM via signal-to-table conversion achieve the best average ranks across prognostic and diagnostic tasks and remain competitive in low-data regimes.
Deep time series models: A comprehensive survey and benchmark
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TA-SparseMG extends SparseTSF with trend-aware reversible instance normalization, scale-adaptive gated denoising, and multiscale gated-attention MLP modules to achieve superior performance on long-term time series forecasting benchmarks.
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Towards Unified and Data-Efficient Prognostics and Health Management with Tabular Foundation Models
Tabular foundation models applied to PHM via signal-to-table conversion achieve the best average ranks across prognostic and diagnostic tasks and remain competitive in low-data regimes.
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TA-SparseMG: Trend-Aware Sparse Forecasting via Multi-Scale Gating for Long-Term Time Series
TA-SparseMG extends SparseTSF with trend-aware reversible instance normalization, scale-adaptive gated denoising, and multiscale gated-attention MLP modules to achieve superior performance on long-term time series forecasting benchmarks.