Publications associées à Comparison of non-parametric T2 relaxometry methods for myelin water quantification

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization

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Towards Trustworthy Deep Learning for Image Reconstruction

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Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

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Spectral Estimators for High-Dimensional Matrix Inference

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In this thesis, we study two closely related directions: robustness and generalization in modern deep learning. Deep learning models based on empirical risk minimization are known to be often non-robust to small, worst-case perturbations known as adversari ...

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Partial discharge localization in power transformer tanks using machine learning methods

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Bayes-optimal Learning of Deep Random Networks of Extensive-width

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Deep Learning Generalization with Limited and Noisy Labels

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(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability

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