Deep Neural Networks

In the past five years, deep learning methods have become state-of-the-art in solving various inverse problems. Before such approaches …

This work presents a novel deep-learning-based pipeline for the inverse problem of image deblurring, leveraging augmentation and …

This thesis investigates several aspects of using data-driven methods for image and signal processing tasks, particularly those aspects …

We study the effects of constrained optimization formulations and Frank-Wolfe algorithms for obtaining interpretable neural network …

This work is concerned with the following fundamental question in scientific machine learning: Can deep-learning-based methods solve …

We give a complete characterisation of families of probability distributions that are invariant under the action of ReLU neural network …