Publisher
Springer Nature Switzerland
Reference29 articles.
1. Assaf, R., Schumann, A.: Explainable deep neural networks for multivariate time series predictions. In: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19, pp. 6488–6490. International Joint Conferences on Artificial Intelligence Organization (2019). https://doi.org/10.24963/ijcai.2019/932
2. Ben David, D., Resheff, Y.S., Tron, T.: Explainable AI and adoption of financial algorithmic advisors: an experimental study, pp. 390–400. Association for Computing Machinery, New York, NY, USA (2021). https://doi.org/10.1145/3461702.3462565
3. Carletti, M., Masiero, C., Beghi, A., Susto, G.A.: Explainable machine learning in industry 4.0: evaluating feature importance in anomaly detection to enable root cause analysis. In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), pp. 21–26 (2019). https://doi.org/10.1109/SMC.2019.8913901
4. Creswell, J.S., David, C.J.: Research Design. Qualitative, quantitative, and mixed method approaches. SAGE Publications, Los Angeles, CA, USA, 5 edn. (2018)
5. Degen, H.: Respect the user’s time: experience architecture and design for efficiency. Helmut Degen, Plainsboro, NJ, USA, 1 edn. (Jun 2022), https://www.designforefficiency.com
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献