Manage settings
MENU
About this site
In het Nederlands
Home
Researchers
Projects
Organisations
Publications
Infrastructure
Contact
Research Explorer
Your browser does not support JavaScript or JavaScript is not enabled. Without JavaScript some functions of this webapplication may be disabled or cause error messages. To enable JavaScript, please consult the manual of your browser or contact your system administrator.
Project
A comparative study of conformal prediction methods for valid uncertainty quantification in machine learning.
Information
Project Team
Organisations
Outputs and Outcomes
Code
DOCT/010473
Duration
24 January 2020 → 25 April 2024 (Defended)
Doctoral researcher
Nicolas Dewolf
Research disciplines
No data available
Project description
No data available