1. On the sensitivity of pose estimation neural networks: rotation parameterizations, Lipschitz constants, and provable bounds;Avant;Automatica,2023
2. Ayhan, M. S., & Berens, P. (2018). Test-time data augmentation for estimation of heteroscedastic aleatoric uncertainty in deep neural networks. In 1st conf. on medical imaging with deep learn.. Amsterdam, The Netherlands: 4–6 Jul.
3. Bayesian frequentist bounds for machine learning and system identification;Baggio;Automatica,2022
4. Pattern recognition and machine learning;Bishop,2006
5. Blundell, C., Cornebise, J., Kavukcuoglu, K., & Wierstra, D. (2015). Weight Uncertainty in Neural Networks. In Proc. of the 32nd int. conf. on mach. learn. (ICML). (pp. 1613–1622). Lille, France: 6–11 Jul.