| Machine learning methods to detect money laundering in the bitcoin blockchain in the presence of label scarcity J Lorenz, MI Silva, D Aparício, JT Ascensão, P Bizarro Proceedings of the first ACM international conference on AI in finance, 1-8, 2020 | 139 | 2020 |
| Interleaved sequence RNNs for fraud detection B Branco, P Abreu, AS Gomes, MSC Almeida, JT Ascensão, P Bizarro Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 77 | 2020 |
| GuiltyWalker: Distance to illicit nodes in the Bitcoin network C Oliveira, J Torres, MI Silva, D Aparício, JT Ascensão, P Bizarro arXiv preprint arXiv:2102.05373, 2021 | 34 | 2021 |
| Anti-money laundering alert optimization using machine learning with graphs AN Eddin, J Bono, D Aparício, D Polido, JT Ascensão, P Bizarro, ... arXiv preprint arXiv:2112.07508, 2021 | 18 | 2021 |
| Active learning for imbalanced data under cold start R Barata, M Leite, R Pacheco, MOP Sampaio, JT Ascensão, P Bizarro Proceedings of the Second ACM International Conference on AI in Finance, 1-9, 2021 | 12 | 2021 |
| Arms: Automated rules management system for fraud detection D Aparício, R Barata, J Bravo, JT Ascensão, P Bizarro arXiv preprint arXiv:2002.06075, 2020 | 8 | 2020 |
| Automated rules management system DO Aparício, RJD Barata, JGSB Ferreira, JTBN Ascensão, PGSR Bizarro US Patent 11,403,644, 2022 | 6 | 2022 |
| Graph traversal for measurement of fraudulent nodes MI Silva, DO Aparício, AN Eddin, J Bono, JTBN Ascensão, PGSR Bizarro US Patent App. 17/553,265, 2022 | 5 | 2022 |
| Machine learning methods to detect money laundering in the bitcoin blockchain in the presence of label scarcity (2020) J Lorenz, MI Silva, D Aparício, JT Ascensão, P Bizarro, JT Ascensão Preprint arXiv, 2005 | 5 | 2005 |
| 2020 J Lorenz, M Silva, D Aparício, J Ascensão Mini-tutorial on explicit (and implicit) renaming macros in CHICKEN. non …, 2009 | 4 | 2009 |
| The GANfather: Controllable generation of malicious activity to improve defence systems RR Pereira, J Bono, JT Ascensão, D Aparício, P Ribeiro, P Bizarro Proceedings of the Fourth ACM International Conference on AI in Finance, 133-140, 2023 | 2 | 2023 |
| From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs AN Eddin, J Bono, D Aparício, H Ferreira, JT Ascensão, P Ribeiro, ... Proceedings of the Fourth ACM International Conference on AI in Finance, 176-184, 2023 | 2 | 2023 |
| Active learning annotation system that does not require historical data MOP Sampaio, JTBN Ascensão, PGSR Bizarro, RJD Barata, MLP Leite, ... US Patent App. 17/331,501, 2021 | 2 | 2021 |
| Finding NeMo: Fishing in banking networks using network motifs X Fontes, D Aparício, MI Silva, B Malveiro, JT Ascensão, P Bizarro arXiv preprint arXiv:2108.04494, 2021 | 2 | 2021 |
| Adversarial training for tabular data with attack propagation TL Melo, J Bravo, MOP Sampaio, P Romano, H Ferreira, JT Ascensão, ... arXiv preprint arXiv:2307.15677, 2023 | 1 | 2023 |
| The GANfather: Controllable generation of malicious activity to expose detection weaknesses and improve defence systems. RR Pereira, J Bono, JT Ascensão, DO Aparicio, PMP Ribeiro, P Bizarro | 1 | 2023 |
| Automatic profile extraction in data streams using recurrent neural networks BJAN de Almeida, J Bono, JTBN Ascensão, PGSR Bizarro US Patent App. 17/586,461, 2022 | 1 | 2022 |
| Discriminative machine learning system for optimization of multiple objectives CA Duarte, JGSB Ferreira, PC Abreu, JPV Caetano, TLE Marquês, ... US Patent App. 17/473,153, 2022 | 1 | 2022 |
| Active learning for online training in imbalanced data streams under cold start R Barata, M Leite, R Pacheco, MOP Sampaio, JT Ascensão, P Bizarro arXiv preprint cs.LG/2107.07724, 2021 | 1 | 2021 |
| Interleaved sequence recurrent neural networks for fraud detection BJAN de Almeida, PC Abreu, ASL Gomes, MSC Almeida, JTBN Ascensão, ... US Patent App. 18/637,142, 2024 | | 2024 |
