| Fault prediction in aircraft engines using self-organizing maps M Cottrell, P Gaubert, C Eloy, D François, G Hallaux, J Lacaille, ... Advances in Self-Organizing Maps: 7th International Workshop, WSOM 2009, St …, 2009 | 60 | 2009 |
| Aircraft engine health monitoring using self-organizing maps E Côme, M Cottrell, M Verleysen, J Lacaille Advances in Data Mining. Applications and Theoretical Aspects: 10th …, 2010 | 42 | 2010 |
| Standardized failure signature for a turbofan engine J Lacaille 2009 IEEE Aerospace conference, 1-8, 2009 | 39 | 2009 |
| Detection of anomalies in an aircraft engine J Lacaille, RN Djiki US Patent 8,744,813, 2014 | 28 | 2014 |
| Expertise transfer and automatic failure classification for the engine start capability system X Flandrois, J Lacaille, JR Masse, A Ausloos AIAA Infotech@ Aerospace Conference and AIAA Unmanned... Unlimited …, 2009 | 27 | 2009 |
| Visual mining and statistics for a turbofan engine fleet J Lacaille, E Côme 2011 Aerospace Conference, 1-8, 2011 | 26 | 2011 |
| Global predictive monitoring system for a manufacturing facility JHN Lacaille US Patent 7,894,926, 2011 | 26 | 2011 |
| Using self-organizing maps for clustering anc labelling aircraft engine data phases C Faure, M Olteanu, JM Bardet, J Lacaille 2017 12th international workshop on self-organizing maps and learning vector …, 2017 | 22 | 2017 |
| Model-based clustering of high-dimensional data streams with online mixture of probabilistic PCA A Bellas, C Bouveyron, M Cottrell, J Lacaille Advances in Data Analysis and Classification 7, 281-300, 2013 | 22 | 2013 |
| Monitoring of an aircraft engine for anticipating maintenance operations JHN Lacaille US Patent 9,176,926, 2015 | 21 | 2015 |
| Identifying failures in an aeroengine J Lacaille US Patent 8,682,616, 2014 | 21 | 2014 |
| Aircraft engine fleet monitoring using self-organizing maps and edit distance E Côme, M Cottrell, M Verleysen, J Lacaille International Workshop on Self-Organizing Maps, 298-307, 2011 | 21 | 2011 |
| An unsupervised diagnosis for process tool fault detection: The flexible golden pattern JÉÔ Lacaille, M Zagrebnov IEEE Transactions on Semiconductor Manufacturing 20 (4), 355-363, 2007 | 21 | 2007 |
| Deep embedded SOM: joint representation learning and self-organization F Forest, M Lebbah, H Azzag, J Lacaille reconstruction 500, 500, 2000 | 20 | 2000 |
| Self organizing star (sos) for health monitoring E Côme, M Cottrell, M Verleysen, J Lacaille European conference on artificial neural networks,, 99-104, 2010 | 18 | 2010 |
| Deep architectures for joint clustering and visualization with self-organizing maps F Forest, M Lebbah, H Azzag, J Lacaille Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2019 …, 2019 | 17 | 2019 |
| Anomaly detection based on confidence intervals using SOM with an application to Health Monitoring A Bellas, C Bouveyron, M Cottrell, J Lacaille Advances in Self-Organizing Maps and Learning Vector Quantization …, 2014 | 17 | 2014 |
| Validation of health-monitoring algorithms for civil aircraft engines J Lacaille 2010 IEEE Aerospace Conference, 1-11, 2010 | 17 | 2010 |
| Trajectory clustering for vibration detection in aircraft engines A Hazan, M Verleysen, M Cottrell, J Lacaille Advances in Data Mining. Applications and Theoretical Aspects: 10th …, 2010 | 17 | 2010 |
| Deep embedded self-organizing maps for joint representation learning and topology-preserving clustering F Forest, M Lebbah, H Azzag, J Lacaille Neural Computing and Applications 33 (24), 17439-17469, 2021 | 16 | 2021 |
marie cottrellSAMM Université Paris 1 Panthéon-SorbonneVerified email at univ-paris1.fr
