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Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics.

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Title: Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics.
Authors: Santamaria-Valenzuela, Inmaculada1, mi.santamaria@upm.es, Rodriguez-Fernandez, Victor1, victor.rfernandez@upm.es, Huertas-Tato, Javier1, javier.huertas.tato@upm.es, Park, Jong Hyuk2, jhpark1@seoultech.ac.kr, Camacho, David1, david.camacho@upm.es
Source: International Journal of Interactive Multimedia & Artificial Intelligence; Jun2026, Vol. 9 Issue 7, p47-66, 20p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
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        Value: 10.9781/ijimai.2026.6558
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      – Code: eng
        Text: English
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        PageCount: 20
        StartPage: 47
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      – TitleFull: Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics.
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            NameFull: Santamaria-Valenzuela, Inmaculada
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            NameFull: Park, Jong Hyuk
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            – D: 01
              M: 06
              Text: Jun2026
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              Y: 2026
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