Articles with public access mandates - José Pereira AmorimLearn more
Not available anywhere: 1
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
Mandates: Fundação para a Ciência e a Tecnologia, Portugal
Available somewhere: 4
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
Mandates: Fundação para a Ciência e a Tecnologia, Portugal, European Commission
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
Mandates: Fundação para a Ciência e a Tecnologia, Portugal
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
Mandates: Fundação para a Ciência e a Tecnologia, Portugal
Missing Image Data Imputation using Variational Autoencoders with Weighted Loss.
RC Pereira, JC Santos, JP Amorim, PP Rodrigues, PH Abreu
ESANN, 475-480, 2020
Mandates: Fundação para a Ciência e a Tecnologia, Portugal
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