With our paper on conformal training, we showed how conformal prediction can be integrated into end-to-end training pipelines. There are so many interesting directions of how to improve and build upon conformal training. Unfortunately, I just do not have the bandwidth to pursue all of them. So, in this article, I want to share some research ideas so others can pick them up.
The code for our ICLR’22 paper on learning optimal conformal classifiers is now available on GitHub. The repository not only includes our implementation of conformal training but also relevant baselines such as coverage training and several conformal predictors for evaluation. Furthermore, it allows to reproduce the majority of experiments from the paper.