| Keywords
|
Evidential deep learning, uncertainty quantification, electronic health records +
|
| Level
|
Master +
|
| OneLineSummary
|
The student will build upon the field of evidential deep learning to identify and understand when the model says 'I don't know' +
|
| Prerequisites
|
Statistics; Neural Networks; Programming (Python or Matlab) +
|
| References
|
Sensoy, Murat, Lance Kaplan, and Melih Kandemir. "Evidential deep learning to quantify classification uncertainty." arXiv preprint arXiv:1806.01768 (2018).
Amini, Alexander, et al. "Deep evidential regression." arXiv preprint arXiv:1910.02600 (2019).
|
| StudentProjectStatus
|
Open +
|
| Supervisors
|
Awais Ashfaq +
, Sławomir Nowaczyk +
|
| TimeFrame
|
2023-2024 +
|
| Title
|
Uncertainty quantification for data driven clinical decision making +
|
| Categories |
StudentProject +
|
| Modification dateThis property is a special property in this wiki.
|
29 September 2023 08:36:57 +
|
