| Federated learning for predicting clinical outcomes in patients with COVID-19 I Dayan, HR Roth, A Zhong, A Harouni, A Gentili, AZ Abidin, A Liu, ... Nature medicine 27 (10), 1735-1743, 2021 | 605 | 2021 |
| Federated learning for breast density classification: A real-world implementation HR Roth, K Chang, P Singh, N Neumark, W Li, V Gupta, S Gupta, L Qu, ... Domain Adaptation and Representation Transfer, and Distributed and …, 2020 | 220 | 2020 |
| A survey on embedding dynamic graphs CDT Barros, MRF Mendonça, AB Vieira, A Ziviani ACM Computing Surveys (CSUR) 55 (1), 1-37, 2021 | 141 | 2021 |
| Federated Learning used for predicting outcomes in SARS-COV-2 patients M Flores, I Dayan, H Roth, A Zhong, A Harouni, A Gentili, A Abidin, A Liu, ... Research Square, 2021 | 55 | 2021 |
| Approximating network centrality measures using node embedding and machine learning MRF Mendonça, AMS Barreto, A Ziviani IEEE Transactions on Network Science and Engineering 8 (1), 220-230, 2020 | 37 | 2020 |
| Simulating human behavior in fighting games using reinforcement learning and artificial neural networks MRF Mendonça, HS Bernardino, RF Neto 2015 14th Brazilian symposium on computer games and digital entertainment …, 2015 | 25 | 2015 |
| Graph-based skill acquisition for reinforcement learning MRF Mendonca, A Ziviani, AMS Barreto ACM Computing Surveys (CSUR) 52 (1), 1-26, 2019 | 16 | 2019 |
| Stealthy path planning using navigation meshes MRF Mendonça, HS Bernardino, RF Neto 2015 Brazilian Conference on Intelligent Systems (BRACIS), 31-36, 2015 | 12 | 2015 |
| Reinforcement learning with optimized reward function for stealth applications MRF Mendonça, HS Bernardino, RF Neto Entertainment Computing 25, 37-47, 2018 | 11 | 2018 |
| A Survey on Embedding Dynamic Graphs. CDT de Barros, MRF Mendonça, AB Vieira, A Ziviani ACM Comput. Surv. 55 (2), 10:1-10:37, 2023 | 6 | 2023 |
| Efficient information diffusion in time-varying graphs through deep reinforcement learning MRF Mendonça, AMS Barreto, A Ziviani World Wide Web 25 (6), 2535-2560, 2022 | 6 | 2022 |
| Regarding “serial quantitative chest CT assessment of COVID-19: deep-learning approach” MS Takahashi, MRF de Mendonça, I Pan, RZ Pinetti, FC Kitamura Radiology: Cardiothoracic Imaging 2 (3), 2020 | 5 | 2020 |
| Abstract state transition graphs for model-based reinforcement learning MRF de Mendonça, A Ziviani, AMS Barreto 2018 7th Brazilian Conference on Intelligent Systems (BRACIS), 115-120, 2018 | 5 | 2018 |
| Network-based procedural story generation MRF Mendonça, A Ziviani Computers in Entertainment (CIE) 16 (3), 1-18, 2018 | 4 | 2018 |
| Federated learning for predicting clinical outcomes in covid-19 patients I Dayan, H Roth, A Zhong, A Harouni, A Gentili, A Abidin, A Liu, AB Costa, ... Nature Medicine, 2021 | 2 | 2021 |
| Laplacian using abstract state transition graphs: A framework for skill acquisition M Mendonça, A Ziviani, A Barreto 2019 8th Brazilian Conference on Intelligent Systems (BRACIS), 263-268, 2019 | 2 | 2019 |
| Methodologic Assessment of a Deep Learning Approach Measuring Lung Opacification in COVID-19 at Chest CT MS Takahashi, M Ribeiro Furtado de Mendonça, I Pan, RZ Pinetti, ... Radiology: Cardiothoracic Imaging 2 (3), e200242, 2020 | | 2020 |
| Entorse de tornozelo: fisiopatologia, diagnóstico, causas, sintomas e tratamento das lesões ligamentares AC Vieira, F Angotti, G Sabino, H Sisnando, M Mendonça, R Adusumilli | | |
| Occlusion of Virtual Objects for Augmented Reality Systems using Kinect JV de Sá Hauck, MRF Mendonca, RLS da Silva | | |
