1. Bandyapadhyay, S., Fomin, F.V., Golovach, P.A., Lochet, W., Purohit, N., Simonov, K.: How to find a good explanation for clustering? Artif. Intell. 322, 103948 (2023)
2. Becker, D., Bremer, V., Funk, B., Asselbergs, J., Riper, H., Ruwaard, J.: How to predict mood? Delving into features of smartphone-based data. In: Twenty-Second Americas Conference on Information Systems, San Diego (2016)
3. Bento, J., Saleiro, P., Cruz, A.F., Figueiredo, M.A., Bizarro, P.: TimeSHAP: explaining recurrent models through sequence perturbations. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 2565–2573 (2021)
4. Bonifati, A., Buono, F.D., Guerra, F., Tiano, D.: Time2Feat: learning interpretable representations for multivariate time series clustering. Proc. VLDB Endow. 16(2), 193–201 (2022)
5. Cuturi, M.: Fast global alignment kernels. In: Proceedings of the 28th International Conference on Machine Learning (ICML-11), pp. 929–936 (2011)