Approximating Viability Kernels With Support Vector Machines. - Guillaume Deffuant; Laetitia Chapel; Sophie Martin (IEEE Trans. Autom. Control., 2007)

Maintenir la viabilité ou la résilience d'un système : les machines à vecteurs de support pour rompre la malédiction de la dimensionnalité ? - Laëtitia Chapel (2007)

Sparse input matrix and state estimation for linear systems. - Laetitia Chapel; Douglas J. Leith (CDC, 2010)

Probabilistic approaches to cheating detection in online games. - Laetitia Chapel; Dmitri Botvich; David Malone (CIG, 2010)

Inner and Outer Capture Basin Approximation with Support Vector Machines. - Laetitia Chapel; Guillaume Deffuant (ICINCO (1), 2011)

A semantic monitoring and management framework for end-to-end services. - John Keeney; Owen Conlan; Viliam Holub; Miao Wang 002; Laetitia Chapel; Martin Serrano; Sven van der Meer (Integrated Network Management, 2011)

Classwise hyperspectral image classification with PerTurbo method. - Laetitia Chapel; Thomas Burger; Nicolas Courty; Sébastien Lefèvre (IGARSS, 2012)

Anomaly Detection with Score Functions Based on the Reconstruction Error of the Kernel PCA. - Laetitia Chapel; Chloé Friguet (ECML/PKDD (1), 2014)

Hyperspectral image classification from multiscale description with constrained connectivity and metric learning. - Sébastien Lefèvre; Laetitia Chapel; François Merciol (WHISPERS, 2014)

PerTurbo Manifold Learning Algorithm for Weakly Labeled Hyperspectral Image Classification. - Laetitia Chapel; Thomas Burger; Nicolas Courty; Sébastien Lefèvre (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014)

A Subpath Kernel for Learning Hierarchical Image Representations. - Yanwei Cui; Laetitia Chapel; Sébastien Lefèvre (GbRPR, 2015)

Dense Bag-of-Temporal-SIFT-Words for Time Series Classification. - Adeline Bailly; Simon Malinowski; Romain Tavenard; Laetitia Chapel; Thomas Guyet (AALTD@PKDD/ECML (Revised Selected Papers), 2015)

Bag-of-Temporal-SIFT-Words for Time Series Classification. - Adeline Bailly; Simon Malinowski; Romain Tavenard; Thomas Guyet; Lætitia Chapel (AALTD@PKDD/ECML, 2015)

Classification of MODIS time series with Dense Bag-of-Temporal-SIFT-Words: Application to cropland mapping in the Brazilian Amazon. - Adeline Bailly; Damien Arvor; Laetitia Chapel; Romain Tavenard (IGARSS, 2016)

Combining multiscale features for classification of hyperspectral images: A sequence-based kernel approach. - Yanwei Cui; Laetitia Chapel; Sébastien Lefèvre (WHISPERS, 2016)

Combining multiple resolutions into hierarchical representations for kernel-based image classification. - Yanwei Cui; Sébastien Lefèvre; Laetitia Chapel; Anne Puissant (CoRR, 2016)

Efficient Temporal Kernels Between Feature Sets for Time Series Classification. - Romain Tavenard; Simon Malinowski; Laetitia Chapel; Adeline Bailly; Heider Sanchez; Benjamin Bustos (ECML/PKDD (2), 2017)

Nonlinear Time-Series Adaptation for Land Cover Classification. - Adeline Bailly; Laetitia Chapel; Romain Tavenard; Gustau Camps-Valls (IEEE Geosci. Remote. Sens. Lett., 2017)

Scalable Bag of Subpaths Kernel for Learning on Hierarchical Image Representations and Multi-Source Remote Sensing Data Classification. - Yanwei Cui; Laetitia Chapel; Sébastien Lefèvre (Remote. Sens., 2017)

Optimal Transport for structured data. - Titouan Vayer; Laetitia Chapel; Rémi Flamary; Romain Tavenard; Nicolas Courty (CoRR, 2018)

Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties. - Titouan Vayer; Laetitia Chapel; Rémi Flamary; Romain Tavenard; Nicolas Courty (CoRR, 2018)

Optimal Transport for structured data with application on graphs. - Titouan Vayer; Nicolas Courty; Romain Tavenard; Laetitia Chapel; Rémi Flamary (ICML, 2019)

Sliced Gromov-Wasserstein. - Titouan Vayer; Rémi Flamary; Nicolas Courty; Romain Tavenard; Laetitia Chapel (NeurIPS, 2019)

Partial Optimal Tranport with applications on Positive-Unlabeled Learning. - Laetitia Chapel; Mokhtar Z. Alaya; Gilles Gasso (NeurIPS, 2020)

Fused Gromov-Wasserstein Distance for Structured Objects. - Titouan Vayer; Laetitia Chapel; Rémi Flamary; Romain Tavenard; Nicolas Courty (Algorithms, 2020)

Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning. - Laetitia Chapel; Mokhtar Z. Alaya; Gilles Gasso (CoRR, 2020)

Unbalanced Optimal Transport through Non-negative Penalized Linear Regression. - Laetitia Chapel; Rémi Flamary; Haoran Wu; Cédric Févotte; Gilles Gasso (NeurIPS, 2021)

POT: Python Optimal Transport. - Rémi Flamary; Nicolas Courty; Alexandre Gramfort; Mokhtar Z. Alaya; Aurélie Boisbunon; Stanislas Chambon; Laetitia Chapel; Adrien Corenflos; Kilian Fatras; Nemo Fournier; Léo Gautheron; Nathalie T. H. Gayraud; et al. (J. Mach. Learn. Res., 2021)

Machine learning for structured data. (Apprentissage machine pour données structurées). - Laetitia Chapel (2022)

A Hierarchical Prototypical Network for Few-Shot Remote Sensing Scene Classification. - Manal Hamzaoui; Laetitia Chapel; Minh-Tan Pham; Sébastien Lefèvre (ICPRAI (2), 2022)

Time Series Alignment with Global Invariances. - Titouan Vayer; Romain Tavenard; Laetitia Chapel; Rémi Flamary; Nicolas Courty; Yann Soullard (Trans. Mach. Learn. Res., 2022)

Hyperbolic Variational Auto-Encoder for Remote Sensing Scene Embeddings. - Manal Hamzaoui; Laetitia Chapel; Minh-Tan Pham; Sébastien Lefèvre (IGARSS, 2023)

Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics. - Guillaume Mahey; Laetitia Chapel; Gilles Gasso; Clément Bonet; Nicolas Courty (NeurIPS, 2023)

Match-And-Deform: Time Series Domain Adaptation Through Optimal Transport and Temporal Alignment. - François Painblanc; Laetitia Chapel; Nicolas Courty; Chloé Friguet; Charlotte Pelletier; Romain Tavenard (ECML/PKDD (5), 2023)

Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections. - Clément Bonet; Laetitia Chapel; Lucas Drumetz; Nicolas Courty (TAG-ML, 2023)

Fast Optimal Transport through Sliced Wasserstein Generalized Geodesics. - Guillaume Mahey; Laetitia Chapel; Gilles Gasso; Clément Bonet; Nicolas Courty (CoRR, 2023)

Scalable clustering of segmented trajectories within a continuous time framework: application to maritime traffic data. - Pierre Gloaguen; Laetitia Chapel; Chloé Friguet; Romain Tavenard (Mach. Learn., 2023)

Horospherical Learning with Smart Prototypes. - Paul Berg; Björn Michele; Minh-Tan Pham; Laetitia Chapel; Nicolas Courty (BMVC, 2024)

Hyperbolic prototypical network for few shot remote sensing scene classification. - Manal Hamzaoui; Laetitia Chapel; Minh-Tan Pham; Sébastien Lefèvre (Pattern Recognit. Lett., 2024)

One for all and all for one: Efficient computation of partial Wasserstein distances on the line. - Laetitia Chapel; Romain Tavenard (ICLR, 2025)

Bridging Arbitrary and Tree Metrics via Differentiable Gromov Hyperbolicity. - Pierre Houedry; Nicolas Courty; Florestan Martin-Baillon; Laetitia Chapel; Titouan Vayer (CoRR, 2025)

Differentiable Generalized Sliced Wasserstein Plans. - Laetitia Chapel; Romain Tavenard; Samuel Vaiter (CoRR, 2025)