| AmnioML: amniotic fluid segmentation and volume prediction with uncertainty quantification D Csillag, LM Paes, T Ramos, JV Romano, R Schuller, RB Seixas, ... Proceedings of the AAAI Conference on Artificial Intelligence 37 (13), 15494 …, 2023 | 4 | 2023 |
| Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity Analysis D Csillag, CJ Struchiner, GT Goedert arXiv preprint arXiv:2405.09516, 2024 | | 2024 |
| Pós-COVID na Atenção Primária à Saúde: desafios e lições aprendidas AC Vidor, K Oliveira, GT Goedert, J Genari, D Csillag Pós-COVID na Atenção Primária à Saúde e ambulatorial especializada, 63, 2024 | | 2024 |
| SARS-CoV-2 transmission in a highly vulnerable population of Brazil: results from a household longitudinal study L Coelho, P Luz, D Pires, E Jalil, H Perazzo, T Torres, S CARDOSO, ... | | 2023 |
| ExactBoost: Directly Boosting the Margin in Combinatorial and Non-decomposable Metrics D Csillag, C Piazza, T Ramos, JV Romano, RI Oliveira, P Orenstein International Conference on Artificial Intelligence and Statistics, 9017-9049, 2022 | | 2022 |
| Uncertainty Quantification for Amniotic Fluid Segmentation and Volume Prediction D Csillag, L Monteiro, T Ramos, JV Romano, R Schuller, RI Oliveira, ... | | |
| Optimizing Combinatorial and Non-decomposable Metrics with ExactBoost D Csillag, C Piazza, T Ramos, JV Romano, R Oliveira, P Orenstein | | |
