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Time series classification is an important data mining task that has received a lot of interest in the past two decades.
Dynamic-programming approach to continuous speech recognition
Sakoe, H. 1971 · 1971
Earlier work this paper cites.
Efficient retrieval of similar time sequences under time warping
Yi, B.-K.; Jagadish, H. V.; and Faloutsos, C. 1998 · 1998
Earlier work this paper cites.
An index-based approach for similarity search supporting time warping in large sequence databases
Kim, S.-W.; Park, S.; and Chu, W. W. 2001 · 2001
Earlier work this paper cites.
Exact indexing of dynamic time warping
Keogh, E.; and Ratanamahatana, C. A. 2005 · 2005
Earlier work this paper cites.
Semi-supervised time series classification
Wei, L.; and Keogh, E. 2006 · 2006
Cited alongside, same era.
Deep residual learning for image recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
Kipf, T. N.; and Welling, M. 2016 · 2016
Cited alongside, same era.
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
Bagnall, A.; Lines, J.; Bostrom, A.; Large, J.; and Keogh, E. 2017 · 2017
Cited alongside, same era.
The UCR time series archive
Dau, H. A.; Bagnall, A.; Kamgar, K.; Yeh, C.-C. M.; Zhu, Y.; Gharghabi, S.; Ratanamahatana, C. A.; and Keogh, E. 2019 · 2019
Later among the works it cites.
Tapnet: Multivariate time series classification with attentional prototypical network
Zhang, X.; Gao, Y.; Lin, J.; and Lu, C.-T. 2020 · 2020
Later among the works it cites.
An Empirical Study of Graph-Based Approaches for Semi-Supervised Time Series Classification
Alfke, D.; Gondos, M.; Peroche, L.; and Stoll, M. 2021 · 2021
Later among the works it cites.
Towards similarity-aware time-series classification
Zha, D.; Lai, K.-H.; Zhou, K.; and Hu, X. 2022 · 2022
Later among the works it cites.
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