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Reda Chhaibi

2 accepted papers

2024

Combining Statistical Depth and Fermat Distance for Uncertainty Quantification

NeurIPS 2024poster

We measure the out-of-domain uncertainty in the prediction of Neural Networks using a statistical notion called "Lens Depth'' (LD) combined with Fermat Distance, which is able to capture precisely the "depth'' of a point with respect to a distribution in feature space, without any distributional ass…

Cited by 0SourcePDFScholar
2022

Free Probability for predicting the performance of feed-forward fully connected neural networks

NeurIPS 2022accept

Gradient descent during the learning process of a neural network can be subject to many instabilities. The spectral density of the Jacobian is a key component for analyzing stability. Following the works of Pennington et al., such Jacobians are modeled using free multiplicative convolutions from Fre…

Cited by 4SourcePDFScholar