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 | 124 | 2020 |
Two betweenness centrality measures based on randomized shortest paths I Kivimäki, B Lebichot, J Saramäki, M Saerens Scientific reports 6 (1), 19668, 2016 | 75 | 2016 |
A graph-based, semi-supervised, credit card fraud detection system B Lebichot, F Braun, O Caelen, M Saerens International Workshop on Complex Networks and their Applications, 721-733, 2016 | 66 | 2016 |
Incremental learning strategies for credit cards fraud detection B Lebichot, GM Paldino, W Siblini, L He-Guelton, F Oblé, G Bontempi International Journal of Data Science and Analytics 12 (2), 165-174, 2021 | 44 | 2021 |
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 | 24 | 2017 |
Transfer learning strategies for credit card fraud detection B Lebichot, T Verhelst, YA Le Borgne, L He-Guelton, F Oble, G Bontempi IEEE access 9, 114754-114766, 2021 | 20 | 2021 |
AST-MTL: an attention-based multi-task learning strategy for traffic forecasting G Buroni, B Lebichot, G Bontempi IEEE access 9, 77359-77370, 2021 | 20 | 2021 |
Reproducible machine learning for credit card fraud detection-practical handbook YA Le Borgne, W Siblini, B Lebichot, G Bontempi Université Libre de Bruxelles, 2022 | 19 | 2022 |
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 | 18 | 2013 |
Towards refined classifications driven by shap explanations Y Arslan, B Lebichot, K Allix, L Veiber, C Lefebvre, A Boytsov, A Goujon, ... International Cross-Domain Conference for Machine Learning and Knowledge …, 2022 | 15 | 2022 |
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 | 12 | 2020 |
A bag-of-paths node criticality measure B Lebichot, M Saerens Neurocomputing 275, 224-236, 2018 | 12 | 2018 |
The role of diversity and ensemble learning in credit card fraud detection GM Paldino, B Lebichot, YA Le Borgne, W Siblini, F Oblé, G Boracchi, ... Advances in Data Analysis and Classification 18 (1), 193-217, 2024 | 11 | 2024 |
Reproducible Machine Learning for Credit Card Fraud Detection-Practical Handbook. Université Libre de Bruxelles (2022) YA Le Borgne, W Siblini, B Lebichot, G Bontempi | 11 | |
Comparing multilingual and multiple monolingual models for intent classification and slot filling C Lothritz, K Allix, B Lebichot, L Veiber, TF Bissyandé, J Klein International Conference on Applications of Natural Language to Information …, 2021 | 10 | 2021 |
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 BNAIC/BENELEARN, 2019 | 8 | 2019 |
Luxembert: Simple and practical data augmentation in language model pre-training for luxembourgish C Lothritz, B Lebichot, K Allix, L Veiber, TFDA Bissyande, J Klein, ... Proceedings of the Language Resources and Evaluation Conference, 2022, 5080-5089, 2022 | 7 | 2022 |
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 | 6 | 2020 |
Understanding telecom customer churn with machine learning: from prediction to causal inference T Verhelst, O Caelen, JC Dewitte, B Lebichot, G Bontempi Artificial Intelligence and Machine Learning: 31st Benelux AI Conference …, 2020 | 4 | 2020 |