Feature visualization has gained substantial popularity, particularly af...
Deep neural networks (DNNs) are known to have a fundamental sensitivity ...
State-of-the-art approaches for training Differentially Private (DP) Dee...
Attribution methods are a popular class of explainability methods that u...
We argue that, when learning a 1-Lipschitz neural network with the dual ...
Today's most advanced machine-learning models are hardly scrutable. The ...
Ensuring that a predictor is not biased against a sensible feature is th...
We propose a new framework for robust binary classification, with Deep N...