| SciPy 1.0: fundamental algorithms for scientific computing in Python P Virtanen, R Gommers, TE Oliphant, M Haberland, T Reddy, ... Nature methods 17 (3), 261-272, 2020 | 33047 | 2020 |
| Automatic diagnosis of the 12-lead ECG using a deep neural network AH Ribeiro, MH Ribeiro, GMM Paixão, DM Oliveira, PR Gomes, ... Nature communications 11 (1), 1-9, 2020 | 795 | 2020 |
| Deep neural network-estimated electrocardiographic age as a mortality predictor EM Lima, AH Ribeiro, GMM Paixão, MH Ribeiro, MM Pinto-Filho, ... Nature communications 12 (1), 5117, 2021 | 147 | 2021 |
| Beyond exploding and vanishing gradients: analysing RNN training using attractors and smoothness AH Ribeiro, K Tiels, LA Aguirre, T Schön International Conference on Artificial Intelligence and Statistics, 2370-2380, 2020 | 147 | 2020 |
| Deep convolutional networks in system identification C Andersson, AH Ribeiro, K Tiels, N Wahlström, TB Schön 2019 IEEE 58th Conference on Decision and Control (CDC), 3670-3676, 2019 | 77 | 2019 |
| On the smoothness of nonlinear system identification AH Ribeiro, K Tiels, J Umenberger, TB Schön, LA Aguirre Automatica 121, 109158, 2020 | 73 | 2020 |
| Automated multilabel diagnosis on electrocardiographic images and signals V Sangha, BJ Mortazavi, AD Haimovich, AH Ribeiro, CA Brandt, ... Nature communications 13 (1), 1583, 2022 | 66 | 2022 |
| Tele-electrocardiography and bigdata: The CODE (Clinical Outcomes in Digital Electrocardiography) study ALP Ribeiro, GMM Paixão, PR Gomes, MH Ribeiro, AH Ribeiro, ... Journal of electrocardiology 57, S75-S78, 2019 | 61 | 2019 |
| Detection of left ventricular systolic dysfunction from electrocardiographic images V Sangha, AA Nargesi, LS Dhingra, A Khunte, BJ Mortazavi, AH Ribeiro, ... Circulation 148 (9), 765-777, 2023 | 54 | 2023 |
| Atrial fibrillation risk prediction from the 12-lead electrocardiogram using digital biomarkers and deep representation learning S Biton, S Gendelman, AH Ribeiro, G Miana, C Moreira, ALP Ribeiro, ... European Heart Journal-Digital Health 2 (4), 576-585, 2021 | 50 | 2021 |
| Deep networks for system identification: a survey G Pillonetto, A Aravkin, D Gedon, L Ljung, AH Ribeiro, TB Schön Automatica 171, 111907, 2025 | 28 | 2025 |
| How Convolutional Neural Networks Deal with Aliasing AH Ribeiro, TB Schön ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 26 | 2021 |
| Development and validation of deep learning ECG-based prediction of myocardial infarction in emergency department patients S Gustafsson, D Gedon, E Lampa, AH Ribeiro, MJ Holzmann, TB Schön, ... Scientific Reports 12 (1), 19615, 2022 | 24 | 2022 |
| “Parallel Training Considered Harmful?”: Comparing series-parallel and parallel feedforward network training AH Ribeiro, LA Aguirre Neurocomputing 316, 222-231, 2018 | 21 | 2018 |
| On Merging Feature Engineering and Deep Learning for Diagnosis, Risk Prediction and Age Estimation Based on the 12-Lead ECG E Zvuloni, J Read, AH Ribeiro, ALP Ribeiro, JA Behar IEEE Transactions on Biomedical Engineering, 2023 | 20 | 2023 |
| Overparameterized Linear Regression under Adversarial Attacks AH Ribeiro, TB Schön IEEE Transactions on Signal Processing, 2023 | 17 | 2023 |
| Evaluation of Mortality in Atrial Fibrillation: Clinical Outcomes in Digital Electrocardiography (CODE) Study GMM Paixão, LGS Silva, PR Gomes, EM Lima, MPF Ferreira, DM Oliveira, ... Global Heart 15 (1), 2020 | 17 | 2020 |
| Deep Energy-Based NARX Models JN Hendriks, FK Gustafsson, AH Ribeiro, AG Wills, TB Schön IFAC-PapersOnLine 54 (7), 505-510, 2021 | 16 | 2021 |
| Shooting methods for parameter estimation of output error models AH Ribeiro, LA Aguirre IFAC-PapersOnLine 50 (1), 13998-14003, 2017 | 14 | 2017 |
| First Steps Towards Self-Supervised Pretraining of the 12-Lead ECG D Gedon, AH Ribeiro, N Wahlström, TB Schön 2021 Computing in Cardiology (CinC) 48, 1-4, 2021 | 13 | 2021 |
Thomas SchönProfessor, Uppsala UniversityVerified email at it.uu.se
