| Capsule routing via variational bayes F De Sousa Ribeiro, G Leontidis, S Kollias Proceedings of the AAAI Conference on Artificial Intelligence 34, 3749-3756, 2020 | 97 | 2020 |
| A deep learning approach to anomaly detection in nuclear reactors F Caliva*, F De Sousa Ribeiro*, A Mylonakis, C Demazi’ere, P Vinai, ... IEEE International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 88 | 2018 |
| An end-to-end deep neural architecture for optical character verification and recognition in retail food packaging F De Sousa Ribeiro, L Gong, F Calivá, M Swainson, K Gudmundsson, ... IEEE International Conference on Image Processing (ICIP), 2018 | 45 | 2018 |
| Deep Bayesian Self-Training F De Sousa Ribeiro, F Calivá, M Swainson, K Gudmundsson, G Leontidis, ... Neural Computing and Applications, 1-17, 2019 | 43 | 2019 |
| Introducing routing uncertainty in capsule networks F De Sousa Ribeiro, G Leontidis, S Kollias Advances in Neural Information Processing Systems (NeurIPS), 33, 2020 | 38 | 2020 |
| Towards a deep unified framework for nuclear reactor perturbation analysis F De Sousa Ribeiro, F Calivá, D Chionis, A Dokhane, A Mylonakis, ... IEEE Symposium Series on Computational Intelligence (SSCI), 120-127, 2018 | 27 | 2018 |
| An adaptable deep learning system for optical character verification in retail food packaging F De Sousa Ribeiro, F Caliva, M Swainson, K Gudmundsson, G Leontidis, ... IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 1-8, 2018 | 26 | 2018 |
| Learning with Capsules: A Survey F De Sousa Ribeiro, K Duarte, M Everett, G Leontidis, M Shah arXiv preprint arXiv:2206.02664, 2022 | 17 | 2022 |
| Measuring Axiomatic Soundness of Counterfactual Image Models M Monteiro*, F De Sousa Ribeiro*, N Pawlowski, DC Castro, B Glocker International Conference on Learning Representations (ICLR), 2023 | 15 | 2023 |
| Neutron noise-based anomaly classification and localization using machine learning C Demaziere, A Mylonakis, P Vinai, A Durrant, FDS Ribeiro, J Wingate, ... EPJ Web of Conferences 247, 21004, 2021 | 13 | 2021 |
| High fidelity image counterfactuals with probabilistic causal models FDS Ribeiro, T Xia, M Monteiro, N Pawlowski, B Glocker International Conference on Machine Leaning (ICML), 2023 | 12 | 2023 |
| A causal perspective on dataset bias in machine learning for medical imaging C Jones, DC Castro, F De Sousa Ribeiro, O Oktay, M McCradden, ... Nature Machine Intelligence, 1-9, 2024 | 4 | 2024 |
| Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed M Bernhardt, F De Sousa Ribeiro, B Glocker Transactions on Machine Learning Research (TMLR), 2022 | 4 | 2022 |
| Unsupervised conditional slot attention for object centric learning A Kori, F Locatello, F De Sousa Ribeiro, F Toni, B Glocker International Conference on Learning Representations (ICLR), 2023 | 2 | 2023 |
| No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging C Jones, DC Castro, FDS Ribeiro, O Oktay, M McCradden, B Glocker arXiv preprint arXiv:2307.16526, 2023 | 1 | 2023 |
| Analysing the effectiveness of a generative model for semi-supervised medical image segmentation M Rosnati, F De Sousa Ribeiro, M Monteiro, DC de Castro, B Glocker Proceedings of the 2nd Machine Learning for Health symposium, PMLR, 2022 | 1 | 2022 |
| Counterfactual contrastive learning: robust representations via causal image synthesis M Roschewitz, FDS Ribeiro, T Xia, G Khara, B Glocker arXiv preprint arXiv:2403.09605, 2024 | | 2024 |
| Mitigating attribute amplification in counterfactual image generation T Xia, M Roschewitz, FDS Ribeiro, C Jones, B Glocker arXiv preprint arXiv:2403.09422, 2024 | | 2024 |
| Demystifying Variational Diffusion Models FDS Ribeiro, B Glocker arXiv preprint arXiv:2401.06281, 2024 | | 2024 |
| Demystifying Variational Diffusion Models F De Sousa Ribeiro, B Glocker arXiv e-prints, arXiv: 2401.06281, 2024 | | 2024 |
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