A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration

Ramya Hebbalaguppe, Jatin Prakash, Neelabh Madan +1

Deep Neural Networks ( DNN s) are known to make overconfident mistakes, which makes their use problematic in safety-critical applications. State-of-the-art ( SOTA ) calibration tec…