Structured dropout improves confidence calibration in CNNs by promoting ensemble diversity, with empirical support on SVHN, CIFAR-10, CIFAR-100 and in Bayesian active learning.
Residual networks behave like ensembles of relatively shallow networks
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Confidence Calibration for Convolutional Neural Networks Using Structured Dropout
Structured dropout improves confidence calibration in CNNs by promoting ensemble diversity, with empirical support on SVHN, CIFAR-10, CIFAR-100 and in Bayesian active learning.