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 (EAIS, 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 001; Georgios Leontidis; Xujiong Ye; Stefanos D. Kollias (ICIP, 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 (IJCNN, 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 (SSCI, 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)

Capsule Routing via Variational Bayes. - Fabio De Sousa Ribeiro; Georgios Leontidis; Stefanos D. Kollias (AAAI, 2020)

Introducing Routing Uncertainty in Capsule Networks. - Fabio De Sousa Ribeiro; Georgios Leontidis; Stefanos D. Kollias (NeurIPS, 2020)

Deep Bayesian Self-Training. - Fabio De Sousa Ribeiro; Francesco Calivá; Mark Swainson; Kjartan Gudmundsson; Georgios Leontidis; Stefanos D. Kollias (Neural Comput. Appl., 2020)

Uncertainty and capsule networks for computer vision. - Fabio De Sousa Ribeiro (2021)

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 (ML4H@NeurIPS, 2022)

Learning with Capsules: A Survey. - Fabio De Sousa Ribeiro; Kevin Duarte; Miles Everett; Georgios Leontidis; Mubarak Shah (CoRR, 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)

Measuring axiomatic soundness of counterfactual image models. - Miguel Monteiro; Fabio De Sousa Ribeiro; Nick Pawlowski; Daniel C. Castro; Ben Glocker (ICLR, 2023)

High Fidelity Image Counterfactuals with Probabilistic Causal Models. - Fabio De Sousa Ribeiro; Tian Xia; Miguel Monteiro; Nick Pawlowski; Ben Glocker (ICML, 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)

Grounded Object-Centric Learning. - Avinash Kori; Francesco Locatello; Fabio De Sousa Ribeiro; Francesca Toni; Ben Glocker (ICLR, 2024)

Counterfactual Contrastive Learning: Robust Representations via Causal Image Synthesis. - Mélanie Roschewitz; Fabio De Sousa Ribeiro; Tian Xia; Galvin Khara; Ben Glocker (DEMI@MICCAI, 2024)

Mitigating Attribute Amplification in Counterfactual Image Generation. - Tian Xia; Mélanie Roschewitz; Fabio De Sousa Ribeiro; Charles Jones; Ben Glocker (MICCAI (10), 2024)

Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention. - Avinash Kori; Francesco Locatello; Ainkaran Santhirasekaram; Francesca Toni; Ben Glocker; Fabio De Sousa Ribeiro (NeurIPS, 2024)

Latent 3D Brain MRI Counterfactual. - Wei Peng 009; Tian Xia; Fabio De Sousa Ribeiro; Tomas M. Bosschieter; Ehsan Adeli-Mosabbeb; Qingyu Zhao; Ben Glocker; Kilian M. Pohl (CoRR, 2024)

Object-centric Learning with Capsule Networks: A Survey. - Fabio De Sousa Ribeiro; Kevin Duarte; Miles Everett; Georgios Leontidis; Mubarak Shah (ACM Comput. Surv., 2024)

Rethinking Fair Representation Learning for Performance-Sensitive Tasks. - Charles Jones; Fabio De Sousa Ribeiro; Mélanie Roschewitz; Daniel C. Castro; Ben Glocker (ICLR, 2025)

Demystifying Variational Diffusion Models. - Fabio De Sousa Ribeiro; Ben Glocker (Found. Trends Comput. Graph. Vis., 2025)

Robust image representations with counterfactual contrastive learning. - Mélanie Roschewitz; Fabio De Sousa Ribeiro; Tian Xia; Galvin Khara; Ben Glocker (Medical Image Anal., 2025)

Diffusion Counterfactual Generation with Semantic Abduction. - Rajat Rasal; Avinash Kori; Fabio De Sousa Ribeiro; Tian Xia; Ben Glocker (CoRR, 2025)

Decoupled Classifier-Free Guidance for Counterfactual Diffusion Models. - Tian Xia; Fabio De Sousa Ribeiro; Rajat Rasal; Avinash Kori; Raghav Mehta; Ben Glocker (CoRR, 2025)

CF-Seg: Counterfactuals meet Segmentation. - Raghav Mehta; Fabio De Sousa Ribeiro; Tian Xia; Mélanie Roschewitz; Ainkaran Santhirasekaram; Dominic C. Marshall; Ben Glocker (CoRR, 2025)

Where are we with calibration under dataset shift in image classification? - Mélanie Roschewitz; Raghav Mehta; Fabio De Sousa Ribeiro; Ben Glocker (CoRR, 2025)

Flow Stochastic Segmentation Networks. - Fabio De Sousa Ribeiro; Omar Todd; Charles Jones; Avinash Kori; Raghav Mehta; Ben Glocker (CoRR, 2025)