| Les deux révisions précédentesRévision précédenteProchaine révision | Révision précédente |
| start [2025/09/30 14:42] – [Denys Pommeret] pommeret | start [2026/01/14 23:06] (Version actuelle) – pommeret |
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| ''Publications (assez) récentes :'' | ''Publications les plus récentes :'' |
| * Stocksieker, S. Pommeret, D. Charpentier, A. (2025) ‘’Disentangled Deep Smoothed Bootstrap for Fair Imbalanced Regression’’. KES2025 | * Garcia, T. Oms, L. Milhaud, X. Doglioli, A. Messié, M. Lacour, C. Vandekerkhove, P. Grégori, G. Pommeret, D. (2026) "A statistical approach to unveil phytoplankton adaptation to ocean fronts". ASCMO. |
| * Stocksieker, S. Pommeret, D. Charpentier, A. (2025) ‘’KurtHGR: A Neural Maximal Correlation for Tabular Datasets’’. KES2025 | * Salhi, S. et al. (2025) ‘’ Clinical Evaluation of an Automated Pan-Organ Combined PD-L1 Scoring Using Artificial Intelligence on Immunostained Whole Slide Images’’. ESMO Real World Data and Digital Oncology. |
| * Stocksieker, S., Pommeret, D. (2025) "“SHGR: A generalized Maximal Correlation Coefficient”. Neurips 2025 | * Stocksieker, S. Pommeret, D. Charpentier, A. (2025) ‘’Disentangled Deep Smoothed Bootstrap for Fair Imbalanced Regression’’. KES2025. |
| * Thomas, F., Pommeret, D., Guinaudeau, E., Poulet, B., Salhi, Y., Chetritt, J. (2025) "Coping with inter-observer variability when assessing AI for scoring of HER2-stained whole slides". Journal Clinical of Oncology. | * Stocksieker, S. Pommeret, D. Charpentier, A. (2025) ‘’KurtHGR: A Neural Maximal Correlation for Tabular Datasets’’. KES2025. |
| * Stocksieker, S., Pommeret, D., Charpentier, A. (2024) "Generalized Smoothed Bootstrap for Imbalanced Regression" CIKM 2024 | * Stocksieker, S., Pommeret, D. (2025) "“SHGR: A generalized Maximal Correlation Coefficient”. Neurips 2025. |
| * Stocksieker, S., Pommeret, D., Charpentier, A. (2024) "Data Augmentation with Variational Autoencoder for Imbalanced Dataset" ICONIP 2024 | * Thomas, F., Pommeret, D., Guinaudeau, E., Poulet, B., Salhi, Y., Chetritt, J. (2025) "Coping with inter-observer variability when assessing AI for scoring of HER2-stained whole slides". Journal Clinical of Oncology. |
| * Milhaud, X., Pommeret, D., Salhi, Y., Vandekerkhove, P. (2024) "Contamination-source based K-sample clustering" Journal of Machine Learning Research | * Stocksieker, S., Pommeret, D., Charpentier, A. (2024) "Generalized Smoothed Bootstrap for Imbalanced Regression" CIKM 2024. |
| | * Stocksieker, S., Pommeret, D., Charpentier, A. (2024) "Data Augmentation with Variational Autoencoder for Imbalanced Dataset" ICONIP 2024. |
| | * Milhaud, X., Pommeret, D., Salhi, Y., Vandekerkhove, P. (2024) "Contamination-source based K-sample clustering" Journal of Machine Learning Research. |
| * Stocksieker, S., Pommeret, D., Charpentier, A. (2024) "Generalized Oversampling for Learning from Imbalanced Dataset and Associated Theory: Application in Regression" Transactions on Machine Learning research. | * Stocksieker, S., Pommeret, D., Charpentier, A. (2024) "Generalized Oversampling for Learning from Imbalanced Dataset and Associated Theory: Application in Regression" Transactions on Machine Learning research. |
| * Stocksieker, S., Pommeret, D., Charpentier, A. (2024) "Boarding for ISS: Imbalanced Self-Supervised Discovery of a Scaled Autoencoder for Mixed Tabular Datasets" IEEE WCCI. | * Stocksieker, S., Pommeret, D., Charpentier, A. (2024) "Boarding for ISS: Imbalanced Self-Supervised Discovery of a Scaled Autoencoder for Mixed Tabular Datasets" IEEE WCCI. |
| * Chaire d'Excellence ACTIONS (Actuaries for Change in Technologies and Insurees Opportunities for Next Steps) : https://chaireactions.com/ | * Chaire d'Excellence ACTIONS (Actuaries for Change in Technologies and Insurees Opportunities for Next Steps) : https://chaireactions.com/ |
| * Projet ANR DREAMES https://lmm.univ-lemans.fr/fr/projets-et-chaires/anr-dreames.html | * Projet ANR DREAMES https://lmm.univ-lemans.fr/fr/projets-et-chaires/anr-dreames.html |
| ''Packages :'' | * Projet rODEo de l'IMPT "Ordre et désordre dans un océan turbulent" [[https://rodeo-ocean.mio.osupytheas.fr/?page_id=17]] |
| * Kcop R Package https://cran.r-project.org/web/packages/Kcop/index.html | |
| * Projet rODEo de l'IMPT "Ordre et désordre dans un océan turbulent" [[https://rodeo-ocean.mio.osupytheas.fr/?page_id=17]] | |
| * Réseau Thématique Matrisk [[https://ama-matrisk-2024.sciencesconf.org/]] | * Réseau Thématique Matrisk [[https://ama-matrisk-2024.sciencesconf.org/]] |
| | * Projet Lauréat Fondation SCOR [[https://foundation.scor.com/funded-projects/triangle-free-reserving]] |
| | * Projet Smartprog lauréat France 2030 [[https://www.diadeep.com/blog-test/le-consortium-diadeep-aix-marseille-universite-et-ihp-group-laureat-du-programme-france-2030-avec-le-projet-smartprog-lia-francaise-au-service-de-la-prediction-du-cancer]] |
| | ''Packages :'' |
| | * Kcop R Package [[https://cran.r-project.org/web/packages/Kcop/index.html]] |
| | * admix R Package [[https://cran.r-project.org/web/packages/admix/refman/admix.html]] |
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