This survey and benchmark of deep time series models using the released TSLib library finds that models with specific structures perform well only on distinct analysis tasks.
Himtm: Hierarchical multi-scale masked time series modeling for long-term forecasting
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MSTN claims SOTA across time-series tasks with early temporal pooling, but internal inconsistencies in parameter counts, benchmark tables, and implausible error reductions undermine the central claims.
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Deep Time Series Models: A Comprehensive Survey and Benchmark
This survey and benchmark of deep time series models using the released TSLib library finds that models with specific structures perform well only on distinct analysis tasks.
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MSTN: A Lightweight and Fast Model for General TimeSeries Analysis
MSTN claims SOTA across time-series tasks with early temporal pooling, but internal inconsistencies in parameter counts, benchmark tables, and implausible error reductions undermine the central claims.