| Deep-learning domain adaptation techniques for credit cards fraud detection B Lebichot, YA Le Borgne, L He-Guelton, F Oblé, G Bontempi Recent Advances in Big Data and Deep Learning: Proceedings of the INNS Big …, 2020 | 104 | 2020 |
| Two betweenness centrality measures based on randomized shortest paths I Kivimäki, B Lebichot, J Saramäki, M Saerens Scientific reports 6 (1), 1-15, 2016 | 59 | 2016 |
| A graph-based, semi-supervised, credit card fraud detection system B Lebichot, F Braun, O Caelen, M Saerens Complex Networks & Their Applications V: Proceedings of the 5th …, 2017 | 47 | 2017 |
| Incremental learning strategies for credit cards fraud detection B Lebichot, GM Paldino, G Bontempi, W Siblini, L He-Guelton, F Oblé 2020 IEEE 7th international conference on data science and advanced …, 2020 | 22 | 2020 |
| Improving card fraud detection through suspicious pattern discovery F Braun, O Caelen, EN Smirnov, S Kelk, B Lebichot Advances in Artificial Intelligence: From Theory to Practice: 30th …, 2017 | 17 | 2017 |
| Semisupervised classification through the bag-of-paths group betweenness B Lebichot, I Kivimäki, K Françoisse, M Saerens IEEE Transactions on Neural Networks and Learning Systems 25 (6), 1173-1186, 2013 | 17 | 2013 |
| Reproducible Machine Learning for Credit Card Fraud Detection-Practical Handbook. Université Libre de Bruxelles (2022) YA Le Borgne, W Siblini, B Lebichot, G Bontempi | 12 | |
| Ast-mtl: An attention-based multi-task learning strategy for traffic forecasting G Buroni, B Lebichot, G Bontempi IEEE access 9, 77359-77370, 2021 | 11 | 2021 |
| Graph-based fraud detection with the free energy distance S Courtain, B Lebichot, I Kivimäki, M Saerens Complex Networks and Their Applications VIII: Volume 2 Proceedings of the …, 2020 | 10 | 2020 |
| A bag-of-paths node criticality measure B Lebichot, M Saerens Neurocomputing 275, 224-236, 2018 | 10 | 2018 |
| A constrained randomized shortest-paths framework for optimal exploration B Lebichot, G Guex, I Kivimäki, M Saerens arXiv preprint arXiv:1807.04551, 2018 | 9 | 2018 |
| Stochastic constraint propagation for mining probabilistic networks ALD Latour, B Babaki, S Nijssen, K Beuls, B Bogaerts, G Bontempi, ... Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC …, 2019 | 8 | 2019 |
| Transfer learning strategies for credit card fraud detection B Lebichot, T Verhelst, YA Le Borgne, L He-Guelton, F Oblé, G Bontempi IEEE access 9, 114754-114766, 2021 | 5 | 2021 |
| Comparing multilingual and multiple monolingual models for intent classification and slot filling C Lothritz, K Allix, B Lebichot, L Veiber, TF Bissyandé, J Klein Natural Language Processing and Information Systems: 26th International …, 2021 | 5 | 2021 |
| An experimental study of graph-based semi-supervised classification with additional node information B Lebichot, M Saerens Knowledge and Information Systems 62 (11), 4337-4371, 2020 | 5 | 2020 |
| On the suitability of SHAP explanations for refining classifications Y Arslan, B Lebichot, K Allix, L Veiber, C Lefebvre, A Boytsov, A Goujon, ... In Proceedings of the 14th International Conference on Agents and Artificial …, 2022 | 3 | 2022 |
| Network analysis based on bag-of-paths: classification, node criticality and randomized policies. B Lebichot Catholic University of Louvain, Louvain-la-Neuve, Belgium, 2018 | 3 | 2018 |
| Transfer learning for credit card fraud detection: A journey from research to production W Siblini, G Coter, R Fabry, L He-Guelton, F Oblé, B Lebichot, ... arXiv preprint arXiv:2107.09323, 2021 | 2 | 2021 |
| Artificial Intelligence and Machine Learning B Bogaerts, G Bontempi, P Geurts, N Harley, B Lebichot, T Lenaerts, ... | 2 | 2021 |
| Modelling Mutually Interactive Fictional Character Conversational Agents. T Winters BNAIC/BENELEARN, 2019 | 2 | 2019 |
Gianluca BontempiUniversité Libre de BruxellesVerified email at ulb.ac.be
