Constrained distance based clustering for time-series: a comparative and experimental study. - Thomas Andrew Lampert; Thi-Bich-Hanh Dao; Baptiste Lafabregue; Nicolas Serrette; Germain Forestier; Bruno Crémilleux; Christel Vrain; Pierre Gançarski (Data Min. Knowl. Discov., 2018)

Constrained Distance based K-Means Clustering for Satellite Image Time-Series. - Thomas Andrew Lampert; Baptiste Lafabregue; Pierre Gançarski (IGARSS, 2019)

Deep Constrained Clustering applied to Satellite Image Time Series. - Baptiste Lafabregue; Jonathan Weber; Pierre Gançarski; Germain Forestier (MACLEAN@PKDD/ECML, 2019)

Constrained Distance-Based Clustering for Satellite Image Time-Series. - Thomas Andrew Lampert; Baptiste Lafabregue; Thi-Bich-Hanh Dao; Nicolas Serrette; Christel Vrain; Pierre Gançarski (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2019)

FODOMUST - Une plateforme de clustering collaboratif sous contraintes incrémental de séries temporelles. - Pierre Gançarski; Baptiste Lafabregue; Abdoul-Djawadou Salaou; Harrison Vernier (EGC, 2020)

Grad Centroid Activation Mapping for Convolutional Neural Networks. - Baptiste Lafabregue; Jonathan Weber; Pierre Gançarski; Germain Forestier (ICTAI, 2021)

Clustering et apprentissage profond sous contraintes pour l'analyse de séries temporelles: application à l'analyse temporelle incrémentale en télédétection. (Constrained clustering and deep learning for time series analysis: with application to incremental temporal analysis for remote sensing). - Baptiste Lafabregue (2021)

Incremental constrained clustering with application to remote sensing images time series. - Baptiste Lafabregue; Pierre Gançarski; Jonathan Weber; Germain Forestier (ICDM (Workshops), 2022)

Deep Clustering Methods Study Applied to Satellite Images Time Series. - Baptiste Lafabregue; Anne Puissant; Jonathan Weber; Germain Forestier (IGARSS, 2022)

End-to-end deep representation learning for time series clustering: a comparative study. - Baptiste Lafabregue; Jonathan Weber; Pierre Gançarski; Germain Forestier (Data Min. Knowl. Discov., 2022)

Écrêter la valeur cible ou filtrer les données en maintenance prévisionnelle : exemple de C-MAPSS. - Nassime Mountasir; Baptiste Lafabregue; Bruno Albert; Nicolas Lachiche (EGC, 2024)

Apprendre avec peu d'exemples : Une approche auto-supervisée basée sur les segments avec application à la télédétection. - Antoine Saget; Baptiste Lafabregue; Antoine Cornuéjols; Pierre Gançarski (EGC, 2025)

Resampling Augmentation for Time Series Contrastive Learning: Application to Remote Sensing. - Antoine Saget; Baptiste Lafabregue; Antoine Cornuéjols; Pierre Gançarski (CoRR, 2025)