Project descriptor: This project explores how machine learning models can estimate uncertainty in their predictions and use a reject option, allowing the model to abstain from making predictions when confidence is too low. The aim is to improve the reliability and safety of automated decision-making systems.
This project would be ideal for BA ICS/MCS, BA CS (JH), BA CSLL and integrated masters. Experience with python programming and an avid interest in machine learning is desirable. Experience with pytorch and a strong track record of projects on Github is a plus.