Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics
The present study explores the interpretability of latent spaces produced by time series foundation models, focusing on their potential for visual analysis tasks. Specifically, we evaluate the MOMENT family of models, a set of transformer-based, pre-trained architectures for multivariate time serie...
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| 主要な著者: | , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Universidad Internacional de La Rioja (UNIR)
2026-05-01
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| シリーズ: | International Journal of Interactive Multimedia and Artificial Intelligence |
| 主題: | |
| オンライン･アクセス: | https://www.ijimai.org/index.php/ijimai/article/view/6558 |
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