Papers using Aeon¶
This is a list of papers that use aeon. If you have a paper that uses aeon,
please add it to this list by making a pull request. Please include a hyperlink to
the paper and a link to the code in your personal GitHub or other repository.
Classification¶
Middlehurst, M. and Schäfer, P. and Bagnall, A. (2024). Bake off redux: a review and experimental evaluation of recent time series classification algorithms. Data Mining and Knowledge Discovery, online first, open access. Paper Webpage/Code
Clustering¶
Holder, C., Middlehurst, M. and Bagnall, A., (2024). A review and evaluation of elastic distance functions for time series clustering. Knowledge and Information Systems, 66(2), pp.765-809. Paper Webpage/Code
Holder, C., Guijo-Rubio, D. and Bagnall, A., 2023, September. Clustering time series with k-medoids based algorithms. In International Workshop on Advanced Analytics and Learning on Temporal Data (pp. 39-55). Paper
Regression¶
Guijo-Rubio, D., Middlehurst, M., Arcencio, G., Silva, D. and Bagnall, A. (2024). Unsupervised Feature Based Algorithms for Time Series Extrinsic Regression. Data Mining and Knowledge Discovery, online first, open access. Paper Webpage/Code
Middlehurst, M. and Bagnall, A., (2023), September. Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression. In International Workshop on Advanced Analytics and Learning on Temporal Data (pp. 113-126). Paper Webpage/Code
Ordinal classification¶
Ayllón-Gavilán, R., Guijo-Rubio, D., Gutiérrez, P.A., Bagnall, A., and Hervás-Martínez, C. Convolutional and Deep Learning based techniques for Time Series Ordinal Classification. ArXiV.
Ayllón-Gavilán, R., Guijo-Rubio, D., Gutiérrez, P. A., and Hervás-Martínez, C. (2024). O-Hydra: A Hybrid Convolutional and Dictionary-Based Approach to Time Series Ordinal Classification. In Conference of the Spanish Association for Artificial Intelligence (pp. 50-60). Paper.
Ayllón-Gavilán, R., Guijo-Rubio, D., Gutiérrez, P.A., and Hervás-Martínez, C. (2023). A Dictionary-Based Approach to Time Series Ordinal Classification. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2023. Lecture Notes in Computer Science, vol 14135. Paper.
Prototyping¶
Ismail-Fawaz, A. and Ismail Fawaz, H. and Petitjean, F. and Devanne, M. and Weber, J. and Berretti, S. and Webb, GI. and Forestier, G. (2023 December “ShapeDBA: Generating Effective Time Series Prototypes Using ShapeDTW Barycenter Averaging.” ECML/PKDD Workshop on Advanced Analytics and Learning on Temporal Data. Paper code
Holder, C., Guijo-Rubio, D., & Bagnall, A. J. (2023). Barycentre Averaging for the Move-Split-Merge Time Series Distance Measure. In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management-Volume 1:, 51-62, pp. 51-62. Paper