|
| [JOURNAL] | Hyperbolic Prototypical Network for Few Shot Remote Sensing Scene Classification (Manal Hamzaoui, Laetitia Chapel, Minh-Tan Pham, Sébastien Lefèvre), Pattern Recognition Letters, accepted. |
| [PROC] | Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics (Guillaume Mahey, Laetitia Chapel, Gilles Gasso, Clément Bonet, Nicolas Courty), NeurIPS, 2023, [Arxiv], Spotlight. |
| [PROC] | Match-And-Deform: Time Series Domain Adaptation through Optimal Transport and Temporal Alignmentn (François Painblanc, Laetitia Chapel, Nicolas Courty, Chloé Friguet, Charlotte Pelletier, Romain Tavenard), ECML PKDD, 2023, [Arxiv]. |
| [PROC] | Hyperbolic variational auto-encoder for remote sensing scene embeddings (Manal Hamzaoui, Laetitia Chapel, Minh-Tan Pham, Sébastien Lefèvre), IGARSS, 2023, [HAL]. |
| [JOURNAL] | Time series alignment with global invariances (Titouan Vayer, Laetitia Chapel, Nicolas Courty, Rémi Flamary, Romain Tavenard, Yann Soulard), TMLR, 2022 [pdf] |
| [REPORT] | Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections (Clément Bonnet, Laetitia Chapel, Lucas Drumetz, Nicolas Courty), 2022 [Arxiv] |
| [PROC] | A hierarchical prototypical network for few-shot remote sensing scene classification (Manal Hamzaoui, Laetitia Chapel, Minh-Tan Pham, Sébastien Lefèvre), ICPRAI: Pattern Recognition and Artificial Intelligence, Lecture Notes in Computer Science, vol 13364., 2022. [pdf] Best paper award. |
| [PROC] | Unbalanced Optimal Transport through Non-negative Penalized Linear Regression (Laetitia Chapel*, Rémi Flamary*, Haoran Wu, Cédric Févotte, Gilles Gasso), NeurIPS, 2021 [Arxiv](* indicates equal contribution) |
| [JOURNAL] | Scalable clustering of segmented trajectories within a continuous time framework: application to maritime traffic data (Pierre Gloaguen, Laetitia Chapel, Chloé Friguet, Romain Tavenard), Machine learning, 2021. [HAL] |
| [JOURNAL] | POT: Python Optimal Transport (Rémi Flamary and Nicolas Courty and Alexandre Gramfort and Mokhtar Z. Alaya and Aurélie Boisbunon and Stanislas Chambon and Laetitia Chapel et al.), Journal of Machine Learning Research, 22(78), pages 1-8, 2021. [pdf] |
| [PROC] | Partial Optimal Transport with Application on Positive-Unlabeled Learning (Laetitia Chapel, Mokhtar Z. Alaya, Gilles Gasso), NeurIPS, 2020 [pdf] |
| [JOURNAL] | Fused Gromov-Wasserstein distance for structured objects (Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty), Algorithms, special issue Efficient Graph Algorithms in Machine Learning, 2020.[doi] |
| [PROC] | Optimal transport for structured data with applications on graphs (Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty), 36th International Conference on Machine Learning, PMLR 97:6275-6284, 2019.[pdf] |
| [PROC] | Sliced Gromov-Wasserstein (Titouan Vayer, Rémi Flamary, Romain Tavenard, Laetitia Chapel, Nicolas Courty), Advances in Neural Information Processing Systems 32 (NeurIPS), 2019.[pdf] |
| [PROC] | Transport Optimal pour les Signaux sur Graphes (Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty), Colloque Gretsi-Traitement du signal et des images, 2019. |
| [PROC] | Efficient Temporal Kernels between Feature Sets for Time Series Classification (Romain Tavenard, Simon Malinowski, Laetitia Chapel, Adeline Bailly, Heider Sanchez, Benjamin Bustos), European Conference on Machine Learning (ECML PKDD), pp 528-543, 2017.[pdf] |
| [JOURNAL] | Nonlinear Time Series Adaptation for Land Cover Classification (Adeline Bailly, Laetitia Chapel, Romain Tavenard, Gustau Camps-Valls), IEEE Geoscience and Remote Sensing Letters , 14(6), pages 896-900, 2017. [doi] |
| [JOURNAL] | 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 Sensing, 9(3), 2017. [doi] |
| [PROC] | Combining multiscale features for classification of hyperspectral images: a sequence based kernel approach (Yanwei Cui, Laetitia Chapel, Sébastien Lefèvre), Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS), 2016. [doi] |
| [PROC] | Combining Multiple Resolutions into Hierarchical Representations for kernel-based Image Classification (Yanwei Cui, Sébastien Lefèvre, Laetitia Chapel, Anne Puissant), International Conference on Geographic Object-Based Image Analysis (GEOBIA), 2016. [Arxiv] |
| [PROC] | 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), IEEE International conference on Geoscience and Remote Sensing Symposium (IGARSS), pages 2300-2303, 2016. [doi] |
| [CHAPTER] | Dense Bag-of-Temporal-SIFT-Words for Time Series Classification (Adeline Bailly, Simon Malinowski, Romain Tavenard, Laetitia Chapel, Thoma Guyet), LNAI special volume of Advanced Analytics and Learning on Temporal Data (AALTD) 2015 conference 9785, pages 17-30, 2016. [doi] |
| [PROC] | Bag-of-Temporal-SIFT-Words for Time Series Classification (Adeline Bailly, Simon Malinowski, Romain Tavenard, Thomas Guyet, Laetitia Chapel), Proceedings of the 1st ECML/PKDD International Workshop on Advanced Analytics and Learning on Temporal Data, 2015. [pdf] |
| [PROC] | A Subpath Kernel for Learning Hierarchical Image Representations (Yanwei Cui, Laetitia Chapel, Sébastien Lefèvre), Workshop on Graph-based Representations in Pattern Recognition (GbR2015), LNCS 9069, pages 34-43, Springer, 2015. [doi] |
| [PROC] | Anomaly detection with score functions based on the reconstruction error of the kernel PCA (Laetitia Chapel, Chloé Friguet), European Conference on Machine Learning (ECML PKDD), Part I, LNCS 8724, pages 227-241, Springer, 2014. [doi] |
| [JOURNAL] | PerTurbo manifold learning algorithm for weakly labelled hyperspectral image classification (Laetitia Chapel, Thomas Burger, Nicolas Courty, Sébastien Lefèvre), JSTARS, special issue on machine learning, vol. 7, no. 4, pages 1070-1078, 2014. [doi] |
| [PROC] | Hyperspectral Image Classification from Multiscale Description with Constrained Connectivity and Metric Learning (Sébastien Lefèvre, Laetitia Chapel, François Merciol), IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2014. |
| [PROC] | Hyperspectral image representation through α-trees (François Merciol, Laetitia Chapel, Sébastien Lefèvre), Ninth Conference on Image Information Mining, pages 37-40, 2014. [doi] |
| [CHAPTER] | SVM approximation of value function contours in target hitting problems (Laetitia Chapel, Guillaume Deffuant), Lecture Notes in Electrical Engineering, vol. 174, pages 37-48, Springer, 2013. [doi] |
| [PROC] | Représentation d'images hyperspectrales sous forme d'arbres α (François Merciol, Laetitia Chapel, Sébastien Lefèvre), Colloque Gretsi-Traitement du signal et des images, 2013. |
| [PROC] | Classwise hyperspectral image classification with PerTurbo method (Laetitia Chapel, Thomas Burger, Nicolas Courty, Sébastien Lefèvre), IEEE International conference on Geoscience and Remote Sensing Symposium (IGARSS), pages 6883-6886, Springer, 2012. [doi] |
| [PROC] | Inner and outer capture basin approximation with Support Vector Machines (Laetitia Chapel, Guillaume Deffuant), International Conference on Informatics in Control, Automation and Robotics (Icinco), pages 30-40, SciTePress, 2011. [doi] |
| [PROC] | A semantic monitoring and management framework for end-to-end services (John Keeney, Owen Conlan, Vilem Holub, Miao Wang, Laetitia Chapel, Martin Serrano, Sven Van der Meer), IFIP/IEEE International Symposium on Integrated Network Management (IM), pages 658-661, 2011. [doi] |
| [CHAPTER] | Approximating Viability Kernels and Resilience Values: Algorithms and Practical Issues Illustrated with KAVIAR Software (Laetitia Chapel, Guillaume Deffuant), Viability and Resilience of Complex Systems, Deffuant, Guillaume and Gilbert, Nigel eds., pages 161-192, Springer, 2011. [doi] |
| [CHAPTER] | Viability and Resilience in the Dynamics of Language Competition (Xavier Castelló, Federico Vazquez, Víctor M. Eguíluz, Lucía Loureiro-Porto, Maxi San Miguel, Laetitia Chapel, Guillaume Deffuant), Viability and Resilience of Complex Systems, Deffuant, Guillaume and Gilbert, Nigel eds., pages 39-73, Springer, 2011. [doi] |
| [JOURNAL] | Viability and resilience of languages in competition (Laetitia Chapel, Xavier Castelló, Claire Bernard, Guillaume Deffuant, Víctor M. Eguíluz, Sophie Martin, Maxi San Miguel), Plos One, vol. 5, no. 1, pages e8681, 2010. [doi] |
| [PROC] | Sparse input matrix and state estimation for linear systems (Laetitia Chapel, Douglas J. Leith), IEEE International Conference on Decision and Control (CDC), pages 4441-4446, 2010. [doi] |
| [PROC] | Probabilistic approaches to cheating detection in online games (Laetitia Chapel, Dmitri Botvich, David Malone), IEEE Symposium on Computational Intelligence and Games (CIG), pages 195-201, 2010. [doi] |
| [JOURNAL] | Defining yield policies in a viability approach (Laetitia Chapel, Guillaume Deffuant, Sophie Martin, Christian Mullon), Ecological Modelling, vol. 212, no. 1-2, pages 10-15, 2008. [doi] |
| [JOURNAL] | Stream flow scaling properties: investigating characteristic scales from different statistical approaches (Eric Sauquet, Maria-Helena Ramos, Laetitia Chapel, Pietro Bernardara), Hydrological Processes, vol. 22, no. 17, pages 3462-3475, 2008. [doi] |
| [JOURNAL] | Approximating Viability Kernels With Support Vector Machines (Guillaume Deffuant, Laetitia Chapel, Sophie Martin), IEEE Transactions on Automatic Control, vol. 52, no. 5, pages 933-937, 2007. [doi] |
| [THESIS] | Maintenir la viabilité ou la résilience d'un système : les machines à vecteurs de support pour rompre la malédiction de la dimensionnalité ? (Laetitia Chapel), Ph.D. thesis, Université Blaise Pascal, Clermont-Ferrand, 2007. |
| [PROC] | SVM viability controller active learning: Application to bike control (Laetitia Chapel, Guillaume Deffuant), IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL), pages 193-200, 2007.[doi] |
| [PROC] | Lake eutrophication: using resilience evaluation to compute sustainable policies (Laetitia Chapel, Guillaume Deffuant), International Conference on Environmental Science and Technology (CEST), pages A204-211, 2007. |
| [PROC] | SVM viability controller active learning (Laetitia Chapel, Guillaume Deffuant), Kernel machines and reinforcement learning workshop, part of ICML 2006, 2006. |
| [PROC] | Utiliser des Support Vector Machines pour apprendre un noyau de viabilité (Guillaume Deffuant, Sophie Martin, Laetitia Chapel), Manifestation des Jeunes Chercheurs francophones dans les domaines des STIC (MajecSTIC), (best paper award) 2005. |
