TimeSqueeze: Dynamic patching

A mechanism that adaptively selects patch boundaries within each sequence based on local signal complexity. (NeurIPS)

NeurIPS

May 13, 2026

Topics:

Large time series forecasting models are limited by a trade-off between computational cost and preserving critical temporal details. TimeSqueeze is a new hybrid architecture that resolves this issue by using a lightweight encoder and adaptive patching to dynamically compress input data, focusing computation on information-rich regions. This approach significantly reduces computational requirements while improving forecasting accuracy.

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