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Florent Forest
Florent Forest
Scientific collaborator, EPFL (École Polytechnique Fédérale de Lausanne)
Verified email at epfl.ch - Homepage
Title
Cited by
Cited by
Year
GammaLib and ctools-A software framework for the analysis of astronomical gamma-ray data
J Knödlseder, M Mayer, C Deil, JB Cayrou, E Owen, N Kelley-Hoskins, ...
Astronomy & Astrophysics 593, 2016
1142016
Deep Architectures for Joint Clustering and Visualization with Self-Organizing Maps
F Forest, M Lebbah, H Azzag, J Lacaille
PAKDD, Workshop on Learning Data Representations for Clustering (LDRC), 2019
132019
Deep Embedded SOM: Joint Representation Learning and Self-Organization
F Forest, M Lebbah, H Azzag, J Lacaille
ESANN, 131-136, 2019
12*2019
A Generic and Scalable Pipeline for Large-Scale Analytics of Continuous Aircraft Engine Data
F Forest, J Lacaille, M Lebbah, H Azzag
IEEE International Conference on Big Data, 1918-1924, 2018
82018
An Invariance-guided Stability Criterion for Time Series Clustering Validation
F Forest, A Mourer, M Lebbah, H Azzag, J Lacaille
International Conference on Pattern Recognition (ICPR), 2021
72021
A Survey and Implementation of Performance Metrics for Self-Organized Maps
F Forest, M Lebbah, H Azzag, J Lacaille
arXiv preprint arXiv:2011.05847, 2020
62020
Large-scale Vibration Monitoring of Aircraft Engines from Operational Data using Self-organized Models
F Forest, Q Cochard, C Noyer, M Joncour, J Lacaille, M Lebbah, H Azzag
Annual Conference of the PHM Society, 2020
32020
Selecting the Number of Clusters with a Stability Trade-off: an Internal Validation Criterion
A Mourer, F Forest, M Lebbah, H Azzag, J Lacaille
arXiv preprint arXiv:2006.08530, 2020
32020
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
22021
Carte SOM profonde: Apprentissage joint de représentations et auto-organisation
F Forest, M Lebbah, H Azzag, J Lacaille
CAp2020: Conférence d'Apprentissage, 2020
12020
Computing environment system for monitoring aircraft engines
JHN Lacaille, FE Forest
US Patent App. 17/299,249, 2022
2022
Unsupervised Learning of Data Representations and Cluster Structures: Applications to Large-scale Health Monitoring of Turbofan Aircraft Engines
F Forest
Université Sorbonne Paris Nord, 2021
2021
Computer environment system for monitoring aircraft engines
J Lacaille, F Forest
FR Patent FR3,089,501, 2020
2020
GammaLib
R Buehler, F Brun, J Cardenzana, JB Cayrou, C Deil, L Di Venere, ...
2020
CTA Contributions to the 34th International Cosmic Ray Conference (ICRC2015)
JM Martin, M Giroletti, J Ballet, J Ziemann, E Edy, M Grudzinska, E Moretti, ...
2015
CTA Contributions to the 34th International Cosmic Ray Conference (ICRC2015)
TCTA Consortium, A Abchiche, U Abeysekara, Ó Abril, F Acero, ...
arXiv preprint arXiv:1508.05894, 2015
2015
CTA Contributions to the 34th International Cosmic Ray Conference (ICRC2015)
A Abchiche, U Abeysekara, Ó Abril, F Acero, BS Acharya, M Actis, ...
2015
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