2 papers
stat.ML2022
Constructing Prediction Intervals with Neural Networks: An Empirical Evaluation of Bootstrapping and Conformal Inference Methods
Alex Contarino, Christine Schubert Kabban, Chancellor Johnstone +1
Artificial neural networks (ANNs) are popular tools for accomplishing many machine learning tasks, including predicting continuous outcomes. However, the general lack of confidence…
stat.ME2021
Conformal Uncertainty Sets for Robust Optimization
Chancellor Johnstone, Bruce Cox
Decision-making under uncertainty is hugely important for any decisions sensitive to perturbations in observed data. One method of incorporating uncertainty into making optimal dec…