| The NN-Stacking: Feature weighted linear stacking through neural networks V Coscrato, MH de Almeida Inacio, R Izbicki Neurocomputing 399, 141-152, 2020 | 24 | 2020 |
| Estimating and evaluating the uncertainty of rating predictions and top-n recommendations in recommender systems V Coscrato, D Bridge ACM Transactions on Recommender Systems 1 (2), 1-34, 2023 | 16 | 2023 |
| Recommendation uncertainty in implicit feedback recommender systems V Coscrato, D Bridge Irish Conference on Artificial Intelligence and Cognitive Science, 279-291, 2022 | 5 | 2022 |
| Agnostic tests can control the type I and type II errors simultaneously V Coscrato, R Izbicki, RB Stern Brazilian Journal of Probability and Statistics 34 (2), 230-250, 2020 | 5 | 2020 |
| NLS: an accurate and yet easy-to-interpret regression method V Coscrato, MHA Inácio, T Botari, R Izbicki arXiv preprint arXiv:1910.05206, 2019 | 4 | 2019 |
| NLS: An accurate and yet easy-to-interpret prediction method V Coscrato, MHA Inácio, T Botari, R Izbicki Neural Networks 162, 117-130, 2023 | 2 | 2023 |
| Recommender systems V Coscrato, D Bridge, X Li, G Xiao, Y Chen, Z Tang, W Jiang, K Li, X Zhou, ... ACM Transactions on 1 (2), 2023 | 2 | 2023 |
| Interpretable hypothesis tests V Coscrato, LG Esteves, R Izbicki, RB Stern arXiv preprint arXiv:1904.06605, 2019 | 2 | 2019 |
| Supplier Recommendation in Online Procurement V Coscrato, D Bridge arXiv preprint arXiv:2403.01301, 2024 | | 2024 |
| Uncertainty in Recommender Systems V Coscrato University College Cork, 2024 | | 2024 |
| Recommendation uncertainty in implicit feedback Recommender V Coscranto, DG Bridge | | 2022 |
| Neural networks as an optimization method for regression VA Coscrato Universidade de São Paulo, 2019 | | 2019 |
| Neural networks as an optimization tool for regression VA Coscrato | | 2019 |
Rafael IzbickiFederal University of São CarlosVerificeret mail på ufscar.br