no code implementations • 24 Jul 2023 • Jonathan P Williams
Motivated by the need for the development of safe and reliable methods for uncertainty quantification in machine learning, I propose and develop ideas for a model-free statistical framework for imprecise probabilistic prediction inference.
1 code implementation • 4 Nov 2021 • Neil Dey, Jing Ding, Jack Ferrell, Carolina Kapper, Maxwell Lovig, Emiliano Planchon, Jonathan P Williams
In our paper, we propose inductive conformal prediction (ICP) algorithms for the tasks of text infilling and part-of-speech (POS) prediction for natural language data.
1 code implementation • 17 Jul 2018 • Iain Carmichael, Jonathan P Williams
A recent paper presents the "false confidence theorem" (FCT) which has potentially broad implications for statistical inference using Bayesian posterior uncertainty.
Methodology