Fabio De Sousa Ribeiro

According to our database, Fabio De Sousa Ribeiro authored at least 18 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Counterfactual contrastive learning: robust representations via causal image synthesis.

Mélanie Roschewitz, Fabio De Sousa Ribeiro, Tian Xia, Galvin Khara, Ben Glocker

CoRR, 2024

Mitigating attribute amplification in counterfactual image generation.

Tian Xia, Mélanie Roschewitz, Fabio De Sousa Ribeiro, Charles Jones, Ben Glocker

CoRR, 2024

Demystifying Variational Diffusion Models.

Fabio De Sousa Ribeiro, Ben Glocker

CoRR, 2024

2023

No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging.

Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro, Ozan Oktay, Melissa D. McCradden, Ben Glocker

CoRR, 2023

High Fidelity Image Counterfactuals with Probabilistic Causal Models.

Fabio De Sousa Ribeiro, Tian Xia, Miguel Monteiro, Nick Pawlowski, Ben Glocker

Proceedings of the International Conference on Machine Learning, 2023

Measuring axiomatic soundness of counterfactual image models.

Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed.

Melanie Bernhardt, Fabio De Sousa Ribeiro, Ben Glocker

Trans. Mach. Learn. Res., 2022

Learning with Capsules: A Survey.

Fabio De Sousa Ribeiro, Kevin Duarte, Miles Everett, Georgios Leontidis, Mubarak Shah

CoRR, 2022

Analysing the effectiveness of a generative model for semi-supervised medical image segmentation.

Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro, Daniel Coelho de Castro, Ben Glocker

Proceedings of the Machine Learning for Health, 2022

2021

Uncertainty and capsule networks for computer vision.

Fabio De Sousa Ribeiro

PhD thesis, 2021

2020

Deep Bayesian Self-Training.

Fabio De Sousa Ribeiro, Francesco Calivá, Mark Swainson, Kjartan Gudmundsson, Georgios Leontidis, Stefanos D. Kollias

Neural Comput. Appl., 2020

Introducing Routing Uncertainty in Capsule Networks.

Fabio De Sousa Ribeiro, Georgios Leontidis, Stefanos D. Kollias

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Capsule Routing via Variational Bayes.

Fabio De Sousa Ribeiro, Georgios Leontidis, Stefanos D. Kollias

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2018

Deep Bayesian Uncertainty Estimation for Adaptation and Self-Annotation of Food Packaging Images.

Fabio De Sousa Ribeiro, Francesco Calivá, Mark Swainson, Kjartan Gudmundsson, Georgios Leontidis, Stefanos D. Kollias

CoRR, 2018

Towards a Deep Unified Framework for Nuclear Reactor Perturbation Analysis.

Fabio De Sousa Ribeiro, Francesco Calivá, Dionysios Chionis, Abdelhamid Dokhane, Antonios Mylonakis, Christophe Demazière, Georgios Leontidis, Stefanos D. Kollias

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

A Deep Learning Approach to Anomaly Detection in Nuclear Reactors.

Francesco Calivá, Fabio De Sousa Ribeiro, Antonios Mylonakis, Christophe Demazière, Paolo Vinai, Georgios Leontidis, Stefanos D. Kollias

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

An End-to-End Deep Neural Architecture for Optical Character Verification and Recognition in Retail Food Packaging.

Fabio De Sousa Ribeiro, Liyun Gong, Francesco Calivá, Mark Swainson, Kjartan Gudmundsson, Miao Yu, Georgios Leontidis, Xujiong Ye, Stefanos D. Kollias

Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

An adaptable deep learning system for optical character verification in retail food packaging.

Fabio De Sousa Ribeiro, Francesco Calivá, Mark Swainson, Kjartan Gudmundsson, Georgios Leontidis, Stefanos D. Kollias

Proceedings of the 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2018