no code implementations • 20 Sep 2022 • Thomas Buddenkotte, Lorena Escudero Sanchez, Mireia Crispin-Ortuzar, Ramona Woitek, Cathal McCague, James D. Brenton, Ozan Öktem, Evis Sala, Leonardo Rundo
On the contrary, we propose a scalable and intuitive framework to calibrate ensembles of deep learning models to produce uncertainty quantification measurements that approximate the classification probability.