15 citations · 29 across the 7 of their papers we have counts for
7 papers
No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging
Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro +3
As machine learning methods gain prominence within clinical decision-making, addressing fairness concerns becomes increasingly urgent. Despite considerable work dedicated to detect…
Measuring axiomatic soundness of counterfactual image models
Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski +2
We present a general framework for evaluating image counterfactuals. The power and flexibility of deep generative models make them valuable tools for learning mechanisms in structu…
Analysing the effectiveness of a generative model for semi-supervised medical image segmentation
Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro +2
Image segmentation is important in medical imaging, providing valuable, quantitative information for clinical decision-making in diagnosis, therapy, and intervention. The state-of-…
Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed
Melanie Bernhardt, Fabio De Sousa Ribeiro, Ben Glocker
Failure detection in automated image classification is a critical safeguard for clinical deployment. Detected failure cases can be referred to human assessment, ensuring patient sa…
Capsule Routing via Variational Bayes
Fabio De Sousa Ribeiro, Georgios Leontidis, Stefanos Kollias
Capsule networks are a recently proposed type of neural network shown to outperform alternatives in challenging shape recognition tasks. In capsule networks, scalar neurons are rep…
Deep Bayesian Self-Training
Fabio De Sousa Ribeiro, Francesco Caliva, Mark Swainson +3
Supervised Deep Learning has been highly successful in recent years, achieving state-of-the-art results in most tasks. However, with the ongoing uptake of such methods in industria…
Towards a Deep Unified Framework for Nuclear Reactor Perturbation Analysis
Fabio De Sousa Ribeiro, Francesco Caliva, Dionysios Chionis +5
In this paper, we take the first steps towards a novel unified framework for the analysis of perturbations in both the Time and Frequency domains. The identification of type and so…