Rotation2 - Engelhard Lab

Uncertainty estimation in Discrete Time to event models using Evidential Deep Learning

Notebook with code: EDL_DiscreteTImeNN_v2.ipynb

Slide deck with results and plots: UncertaintyEstimation_EDL.pptx

References paper used:

1. Sensoy, M., Kaplan, L., & Kandemir, M. (2018). Evidential deep learning to quantify classification uncertainty. Advances in neural information processing systems, 31.
2. Lee, C., Zame, W., Yoon, J., & Van Der Schaar, M. (2018, April). Deephit: A deep learning approach to survival analysis with competing risks. In Proceedings of the AAAI conference on artificial intelligence (Vol. 32, No. 1).