Trustworthy Artificial Intelligence in the Context of Metrology

Author:

Adel Tameem,Bilson Samuel,Levene Mark,Thompson Andrew

Publisher

Springer Nature Switzerland

Reference61 articles.

1. Antoran, J., Bhatt, U., Adel, T., Weller, A., Hernandez-Lobato, J.: Getting a CLUE: a method for explaining uncertainty estimates. In: International Conference on Learning Representations (ICLR) (2021)

2. Arrieta, A.B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., et al.: Explainable artificial intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI. Inf Fusion 58, 82–115 (2020)

3. Adel, T., Ghahramani, Z., Weller, A.: Discovering interpretable representations for both deep generative and discriminative models. In: International Conference on Machine Learning (ICML), pp. 50–59 (2018)

4. Bich, W., Cox, M.G., Dybkaer, R., Elster, C., et al.: Revision of the ‘Guide to the expression of uncertainty in measurement’. Metrologia 49, 702 (2012)

5. Bommasani, R., Hudson, D.A., Adeli, E., Altman, R., et al.: On the opportunities and risks of foundation models. Mach. Learn. Arch. (2022). arXiv:2108.07258 [cs.LG]

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