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Perturbations, Accuracy and Robustness in Neural Networks
Abstract
A robustness analysis for neural networks, namely the evaluation of the effects induced by perturbations affecting the network weights, is a relevant theoretical aspect since weights characterise the “knowledge space” of the neural model and, hence, its inner nature.
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