Publisher
Springer Nature Switzerland
Reference71 articles.
1. Abrate, C., Bonchi, F.: Counterfactual graphs for explainable classification of brain networks. In: SIGKDD, pp. 2495–2504 (2021)
2. Baldassarre, F., Azizpour, H.: Explainability techniques for graph convolutional networks. arXiv preprint arXiv:1905.13686 (2019)
3. Barabási, A.L., Oltvai, Z.N.: Network biology: understanding the cell’s functional organization. Nat. Rev. Genet. 5(2), 101–113 (2004)
4. Bhatore, S., Mohan, L., Reddy, Y.R.: Machine learning techniques for credit risk evaluation: a systematic literature review. J. Bank. Financ. Technol. 4(1), 111–138 (2020). https://doi.org/10.1007/s42786-020-00020-3
5. Biran, O., Cotton, C.: Explanation and justification in machine learning: a survey. In: IJCAI-17 Workshop on Explainable AI (XAI), vol. 8, pp. 8–13 (2017)