Explainable Time Series Classification
Explainable Time Series Classification is a time series classification paradigm that, as a singular academic concept, belongs to the class of interpretable machine learning methods by virtue of providing human-understandable justifications for its classification decisions while maintaining predictive accuracy.
29
Publications
1.4K
Citations
104
Authors
57
Institutions
Publications per year
2017–2026
28
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XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification
Kevin Fauvel, Tao Lin, Véronique Masson et al. · Mathematics · 2021 · 140 citations · Full text
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Centre National de la Recherche Scientifique
Paris, France
3 h-index
12 publications
972 citations
Université de Rennes
Rennes, France
3 h-index
12 publications
972 citations
Institut de Recherche en Informatique et Systèmes Aléatoires
Rennes, France
3 h-index
12 publications
972 citations
Beijing Jiaotong University
Beijing, China
2 h-index
8 publications
300 citations

University of Pisa
Pisa, Italy
2 h-index
5 publications
326 citations

Stockholm University
Stockholm, Sweden
2 h-index
6 publications
174 citations
Aalto University
Espoo, Finland
2 h-index
2 publications
58 citations
Stony Brook University
Stony Brook, United States
1 h-index
1 publications
94 citations
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3 publications · 191 citations
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2 publications · 72 citations
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2 publications · 107 citations
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2 publications · 256 citations
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CIM · 1 publications · 13 citations
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