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News/MSTN: A Lightweight and Fast Model for General TimeSeries Analysis
arxiv
PublishedApril 14, 2026 at 4:00 AM
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MSTN: A Lightweight and Fast Model for General TimeSeries Analysis

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2511.20577v3 Announce Type: replace Abstract: Real-world time series often exhibit strong non-stationarity, complex nonlinear dynamics, and behavior expressed across multiple temporal scales, from rapid local fluctuations to slow-evolving long-range trends. However, many contemporary architect

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Discussion
Mentioned models
03
  • 01
    Multi-scale Temporal Network (MSTN)
  • 02
    MSTN-BiLSTM
  • 03
    MSTN-Transformer
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#time-series#neural-networks#forecasting#machine-learning

No replies yet. Be first.

Mentioned models
03
  • 01
    Multi-scale Temporal Network (MSTN)
  • 02
    MSTN-BiLSTM
  • 03
    MSTN-Transformer
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#time-series#neural-networks#forecasting#machine-learning

Related coverage

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arxivMAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation2harxivCounterfactual Model Testing Under Distribution Shift2harxivCentralized Critics for N-Agent Ad Hoc Teamwork2harxivWhere and What to Reward? Understanding Generalization Between Verifiable and Open-Ended Domains in Reinforcement Learning2h
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