A global taxonomy of interpretable AI: unifying the terminology for the technical and social sciences M Graziani, L Dutkiewicz, D Calvaresi, JP Amorim, K Yordanova, M Vered, ... Artificial Intelligence Review, 1-32, 2022 | 77 | 2022 |
Evaluation of oversampling data balancing techniques in the context of ordinal classification I Domingues, JP Amorim, PH Abreu, H Duarte, J Santos 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 38 | 2018 |
Evaluating the faithfulness of saliency maps in explaining deep learning models using realistic perturbations JP Amorim, PH Abreu, J Santos, M Cortes, V Vila Information Processing & Management 60 (2), 103225, 2023 | 20 | 2023 |
Interpreting deep machine learning models: an easy guide for oncologists JP Amorim, PH Abreu, A Fernández, M Reyes, J Santos, MH Abreu IEEE Reviews in Biomedical Engineering, 2021 | 14 | 2021 |
Interpreting deep learning models for ordinal problems. JP Amorim, I Domingues, PH Abreu, JAM Santos ESANN, 373-378, 2018 | 14 | 2018 |
Interpretability vs. Complexity: The Friction in Deep Neural Networks JP Amorim, PH Abreu, M Reyes, J Santos 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020 | 11 | 2020 |
An iterative oversampling approach for ordinal classification F Marques, H Duarte, J Santos, I Domingues, JP Amorim, PH Abreu Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, 771-774, 2019 | 10 | 2019 |
Missing Image Data Imputation using Variational Autoencoders with Weighted Loss. RC Pereira, JC Santos, JP Amorim, PP Rodrigues, PH Abreu ESANN, 475-480, 2020 | 7 | 2020 |
Evaluating Post-hoc Interpretability with Intrinsic Interpretability JP Amorim, PH Abreu, J Santos, H Müller arXiv preprint arXiv:2305.03002, 2023 | 1 | 2023 |
Correction to: Interpretable and Annotation-Efficient Learning for Medical Image Computing J Cardoso, H Van Nguyen, N Heller, P Henriques Abreu, I Isgum, W Silva, ... Interpretable and Annotation-Efficient Learning for Medical Image Computing …, 2020 | | 2020 |
Interpretable and Annotation-Efficient Learning for Medical Image Computing: Third International Workshop, iMIMIC 2020, Second International Workshop, MIL3ID 2020, and 5th … J Cardoso, H Van Nguyen, N Heller, PH Abreu, I Isgum, W Silva, R Cruz, ... Springer Nature, 2020 | | 2020 |