Assessing gender bias in machine translation: a case study with google translate MOR Prates, PH Avelar, LC Lamb Neural Computing and Applications 32, 6363-6381, 2020 | 545 | 2020 |
Learning to solve np-complete problems: A graph neural network for decision tsp M Prates, PHC Avelar, H Lemos, LC Lamb, MY Vardi Proceedings of the AAAI conference on artificial intelligence 33 (01), 4731-4738, 2019 | 246 | 2019 |
Graph neural networks meet neural-symbolic computing: A survey and perspective LC Lamb, A Garcez, M Gori, M Prates, P Avelar, M Vardi arXiv preprint arXiv:2003.00330, 2020 | 219 | 2020 |
Graph colouring meets deep learning: Effective graph neural network models for combinatorial problems H Lemos, M Prates, P Avelar, L Lamb 2019 IEEE 31st International Conference on Tools with Artificial …, 2019 | 105 | 2019 |
Superpixel image classification with graph attention networks PHC Avelar, AR Tavares, TLT da Silveira, CR Jung, LC Lamb 2020 33rd SIBGRAPI conference on Graphics, patterns and images (SIBGRAPI …, 2020 | 73 | 2020 |
TIGIT blockade repolarizes AML-associated TIGIT+ M2 macrophages to an M1 phenotype and increases CD47-mediated phagocytosis F Brauneck, B Fischer, M Witt, J Muschhammer, J Oelrich, ... Journal for immunotherapy of cancer 10 (12), e004794, 2022 | 40 | 2022 |
Multitask learning on graph neural networks: Learning multiple graph centrality measures with a unified network P Avelar, H Lemos, M Prates, L Lamb International Conference on Artificial Neural Networks, 701-715, 2019 | 18 | 2019 |
On quantifying and understanding the role of ethics in AI research: A historical account of flagship conferences and journals M Prates, P Avelar, LC Lamb arXiv preprint arXiv:1809.08328, 2018 | 17 | 2018 |
Understanding boolean function learnability on deep neural networks AR Tavares, P Avelar, JM Flach, M Nicolau, LC Lamb, M Vardi arXiv e-prints, arXiv: 2009.05908, 2020 | 16* | 2020 |
Discrete and Continuous Deep Residual Learning over Graphs P Avelar, A Tavares, M Gori, L Lamb 13th International Conference on Agents and Artificial Intelligence 2, 119-131, 2021 | 15 | 2021 |
On the evolution of AI and machine learning: Towards measuring and understanding impact, influence, and leadership at premier AI conferences RB Audibert, H Lemos, P Avelar, AR Tavares, LC Lamb arXiv preprint arXiv:2205.13131, 2022 | 13 | 2022 |
Neural-symbolic relational reasoning on graph models: effective link inference and computation from knowledge bases H Lemos, P Avelar, M Prates, A Garcez, L Lamb International Conference on Artificial Neural Networks, 647-659, 2020 | 8 | 2020 |
Measuring Ethics in AI with AI: A Methodology and Dataset Construction PHC Avelar, RB Audibert, AR Tavares, LC Lamb arXiv preprint arXiv:2107.11913, 2021 | 6 | 2021 |
Incorporating Prior Knowledge in Deep Learning Models via Pathway Activity Autoencoders PH da Costa Avelar, M Wu, S Tsoka arXiv e-prints, arXiv: 2306.05813, 2023 | 3* | 2023 |
On the evolution of Ai and machine learning: Towards a meta-level measuring and understanding impact, influence, and leadership at premier Ai conferences RB Audibert, H Lemos, P Avelar, AR Tavares, LC Lamb arXiv preprint arXiv:2205.13131, 2022 | 3 | 2022 |
Multi-Omic Data Integration and Feature Selection for Patient Stratification via Supervised Concrete Autoencoders PH da Costa Avelar, R Laddach, SN Karagiannis, M Wu, S Tsoka The 8th International Conference on Machine Learning, Optimization, and Data …, 2022 | 3* | 2022 |
Typed graph networks PHC Avelar, H Lemos, MOR Prates, M Gori, L Lamb arXiv preprint arXiv:1901.07984, 2019 | 3 | 2019 |
Solving the kidney exchange problem via graph neural networks with no supervision PF Pimenta, PHC Avelar, LC Lamb Neural Computing and Applications 36 (25), 15373-15388, 2024 | 2 | 2024 |
Learning centrality measures with graph neural networks PHC Avelar | 2 | 2019 |
Weekly Bayesian modelling strategy to predict deaths by COVID-19: A model and case study for the state of Santa Catarina, Brazil PH da Costa Avelar, LC Lamb, S Tsoka, J Cardoso-Silva arXiv preprint arXiv:2104.01133, 0 | 1 | |