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  1. Home
  2. Signal Canvas
  3. TimeSqueeze: Dynamic Patching for Efficient Time Series Fore
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TimeSqueeze: Dynamic Patching for Efficient Time Series Forecasting

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Viability
0.0/10

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Evidence Receipt

Freshness: 2026-04-02T02:30:40.136932+00:00

Claims: 0

References: 0

Proof: pending

Distribution: unknown

Source paper: TimeSqueeze: Dynamic Patching for Efficient Time Series Forecasting

PDF: https://arxiv.org/pdf/2603.11352v1

First buyer signal: unknown

Distribution channel: unknown

Starting…

Dimensions overall score 7.0

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Builds On This
DDiT: Dynamic Patch Scheduling for Efficient Diffusion Transformers
Score 6.0down
Builds On This
Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling
Score 5.0down
Prior Work
IPatch: A Multi-Resolution Transformer Architecture for Robust Time-Series Forecasting
Score 7.0stable
Prior Work
Dynamic Tokenization via Reinforcement Patching: End-to-end Training and Zero-shot Transfer
Score 7.0stable
Prior Work
Video Patch Pruning: Efficient Video Instance Segmentation via Early Token Reduction
Score 7.0stable
Competing Approach
StretchTime: Adaptive Time Series Forecasting via Symplectic Attention
Score 5.0down
Competing Approach
Seg-MoE: Multi-Resolution Segment-wise Mixture-of-Experts for Time Series Forecasting Transformers
Score 7.0stable
Competing Approach
PatchDecomp: Interpretable Patch-Based Time Series Forecasting
Score 5.0down

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