| CATCHM: A novel network-based credit card fraud detection method using node representation learning R Van Belle, B Baesens, J De Weerdt Decision Support Systems 164, 113866, 2023 | 42 | 2023 |
| Inductive graph representation learning for fraud detection R Van Belle, C Van Damme, H Tytgat, J De Weerdt Expert Systems with Applications 193, 116463, 2022 | 19 | 2022 |
| Representation learning in graphs for credit card fraud detection R Van Belle, S Mitrović, J De Weerdt Mining Data for Financial Applications: 4th ECML PKDD Workshop, MIDAS 2019 …, 2020 | 19 | 2020 |
| Defining data quality issues in process mining with IoT data Y Bertrand, R Van Belle, J De Weerdt, E Serral International Conference on Process Mining, 422-434, 2022 | 3 | 2022 |
| Graph representation learning for fraud prediction: A nearest neighbour approach R Van Belle, S Mitrovic, J De Weerdt https://grlearning. github. io/papers/, 2019 | 1 | 2019 |
| SHINE: A Scalable Heterogeneous Inductive Graph Neural Network for Large Imbalanced Datasets R Van Belle, J De Weerdt IEEE Transactions on Knowledge and Data Engineering, 2024 | | 2024 |
| Network Representation Learning for Fraud Detection R Van Belle Network Science Society Conference (NETSCI), 2023 | | 2023 |
| Prof. Dr. Bart Baesens B Baesens, S Höppner, R Van Belle, J De Weerdt, G Deeva, M Snoeck, ... | | |
