Bertrand Lebichot
Bertrand Lebichot
Universite of Luxembourg
Verified email at uni.lu - Homepage
Title
Cited by
Cited by
Year
Two betweenness centrality measures based on randomized shortest paths
I Kivimäki, B Lebichot, J Saramäki, M Saerens
Scientific reports 6 (1), 1-15, 2016
382016
Deep-learning domain adaptation techniques for credit cards fraud detection
B Lebichot, YA Le Borgne, L He-Guelton, F Oblé, G Bontempi
INNS Big Data and Deep Learning conference, 78-88, 2019
332019
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
262016
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
152013
Improving card fraud detection through suspicious pattern discovery
F Braun, O Caelen, EN Smirnov, S Kelk, B Lebichot
International Conference on Industrial, Engineering and Other Applications …, 2017
122017
A bag-of-paths node criticality measure
B Lebichot, M Saerens
Neurocomputing 275, 224-236, 2018
72018
A constrained randomized shortest-paths framework for optimal exploration
B Lebichot, G Guex, I Kivimäki, M Saerens
arXiv preprint arXiv:1807.04551, 2018
42018
Graph-based fraud detection with the free energy distance
S Courtain, B Lebichot, I Kivimäki, M Saerens
International Conference on Complex Networks and Their Applications, 40-52, 2019
32019
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
12020
Network analysis based on bag-of-paths: classification, node criticality and randomized policies
B Lebichot
UCL-Université Catholique de Louvain, 2018
12018
An experimental study of graph-based semi-supervised classification with additional node information
B Lebichot, M Saerens
arXiv preprint arXiv:1705.08716, 2017
12017
Artificial Intelligence and Machine Learning: 31st Benelux AI Conference, BNAIC 2019, and 28th Belgian-Dutch Machine Learning Conference, BENELEARN 2019, Brussels, Belgium …
B Bogaerts, G Bontempi, P Geurts, N Harley, B Lebichot, T Lenaerts, ...
BNAIC 2019, 2021
2021
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, 182-200, 2019
2019
Deep-Learning Domain Adaptation Techniques for Credit Cards Fraud Detection
F Oblé, G Bontempi
Recent Advances in Big Data and Deep Learning: Proceedings of the INNS Big …, 2019
2019
Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019)
K Beuls, B Bogaerts, G Bontempi, P Geurts, N Harley, B Lebichot, ...
BNAIC 2019, 2019
2019
Understanding Telecom Customer Churn with Machine Learning: From Prediction to Causal Inference
B Lebichot, G Bontempi
Artificial Intelligence and Machine Learning: 31st Benelux AI Conference …, 0
Artificial Intelligence and Machine Learning
B Bogaerts, G Bontempi, P Geurts, N Harley, B Lebichot, T Lenaerts, ...
Study of semi-supervised classification algorithms on a graph, based on convolutional neural networks and kernels on graph
S Calbert, M Saerens, B Lebichot
E-commerce Card Fraud Detection Using Big Data/Deep Learning Tools.
H Borgi, B Lebichot
Transfer Learning–An Application of Unsupervised Domain Adaptation
M Desausoi, M Saerens, B Lebichot
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