Browse State-of-the-Art › input filtering
input filtering
3 papers with code · 0 benchmarks · 0 datasets archive 2025-07-28
Input filtering aims to filter out input data that is not necessary for executing model inference, thus reducing data transmission and computing overhead.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
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Datasets archive 2025-07-28
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Most implemented papers archive 2025-07-28
3 shown of 3 papers with code (13 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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28 Sep 2022 3 repositories listedPrevious efforts have tailored effective solutions for many applications, but left two essential questions unanswered: (1) theoretical filterability of an inference workload to guide the application of input filtering…
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23 Apr 2025 1 repository listedModeling path loss in indoor LoRaWAN technology deployments is inherently challenging due to structural obstructions, occupant density and activities, and fluctuating environmental conditions.
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26 Aug 2024 1 repository listedDiffusion-weighted magnetic resonance imaging (dMRI) is the only non-invasive tool for studying white matter tracts and structural connectivity of the brain.
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