Publisher
Springer Nature Switzerland
Reference35 articles.
1. Abdullah, T.A.A., Zahid, M.S.M., Ali, W.: A review of interpretable ml in healthcare: taxonomy, applications, challenges, and future directions. Symmetry 13(12), 2439 (2021). https://doi.org/10.3390/sym13122439
2. Adadi, A., Berrada, M.: Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE Access 6, 52138–52160 (2018). https://doi.org/10.1109/ACCESS.2018.2870052
3. Alvarez-Melis, D., Jaakkola, T.S.: Towards robust interpretability with self-explaining neural networks. In: Proceedings of the 32nd International Conference on Neural Information Processing Systems (NIPS 2018), pp. 7786–7795. Curran Associates Inc., Red Hook (2018)
4. Anello, E., et al.: Anomaly detection for the industrial internet of things: an unsupervised approach for fast root cause analysis. In: 2022 IEEE Conference on Control Technology and Applications (CCTA), pp. 1366–1371 (2022). https://doi.org/10.1109/CCTA49430.2022.9966158
5. Baek, M., Kim, S.B.: Failure detection and primary cause identification of multivariate time series data in semiconductor equipment. IEEE Access 11, 54363–54372 (2023). https://doi.org/10.1109/ACCESS.2023.3281407