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11/18/2022
Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images
This work presents a novel deep-learning-based pipeline for the inverse ...
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12/13/2021
A Complete Characterisation of ReLU-Invariant Distributions
We give a complete characterisation of families of probability distribut...
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10/15/2021
Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings
We study the effects of constrained optimization formulations and Frank-...
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06/01/2021
AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry
This report is dedicated to a short motivation and description of our co...
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11/09/2020
Solving Inverse Problems With Deep Neural Networks – Robustness Included?
In the past five years, deep learning methods have become state-of-the-a...
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03/27/2020
Interval Neural Networks as Instability Detectors for Image Reconstructions
This work investigates the detection of instabilities that may occur whe...
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03/25/2020
Interval Neural Networks: Uncertainty Scores
We propose a fast, non-Bayesian method for producing uncertainty scores ...
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05/27/2019
A Rate-Distortion Framework for Explaining Neural Network Decisions
We formalise the widespread idea of interpreting neural network decision...
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05/22/2019
The Computational Complexity of Understanding Network Decisions
For a Boolean function Φ{0,1}^d→{0,1} and an assignment to its variables...
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01/17/2019