Binary partition tree-based local spectral unmixing. - Lucas Drumetz; Miguel Angel Veganzones; Ruben Marrero; Guillaume Tochon; Mauro Dalla Mura; Antonio Plaza; Jocelyn Chanussot (WHISPERS, 2014)

A new extended linear mixing model to address spectral variability. - Miguel Angel Veganzones; Lucas Drumetz; Guillaume Tochon; Mauro Dalla Mura; Antonio Plaza; José M. Bioucas-Dias; Jocelyn Chanussot (WHISPERS, 2014)

Blind hyperspectral unmixing using an extended linear mixing model to address spectral variability. - Lucas Drumetz; Simon Henrot; Miguel Angel Veganzones; Jocelyn Chanussot; Christian Jutten (WHISPERS, 2015)

Semiautomatic classification of cementitious materials using scanning electron microscope images. - Lucas Drumetz; Mauro Dalla Mura; Samuel Meulenyzer; Sébastien Lombard; Jocelyn Chanussot (J. Electronic Imaging, 2015)

Canonical polyadic decomposition of hyperspectral patch tensors. - Miguel Angel Veganzones; Jeremy E. Cohen; Rodrigo Cabral Farias; Konstantin Usevich; Lucas Drumetz; Jocelyn Chanussot; Pierre Comon (EUSIPCO, 2016)

Hyperspectral unmixing with material variability using social sparsity. - Travis R. Meyer; Lucas Drumetz; Jocelyn Chanussot; Andrea L. Bertozzi; Christian Jutten (ICIP, 2016)

Variability of the endmembers in spectral unmixing: Recent advances. - Lucas Drumetz; Jocelyn Chanussot; Christian Jutten (WHISPERS, 2016)

From local to global unmixing of hyperspectral images to reveal spectral variability. - Guillaume Tochon; Lucas Drumetz; Miguel Angel Veganzones; Mauro Dalla Mura; Jocelyn Chanussot (WHISPERS, 2016)

Hyperspectral Local Intrinsic Dimensionality. - Lucas Drumetz; Miguel Angel Veganzones; Ruben Marrero Gomez; Guillaume Tochon; Mauro Dalla Mura; Giorgio A. Licciardi; Christian Jutten; Jocelyn Chanussot (IEEE Trans. Geosci. Remote. Sens., 2016)

Blind Hyperspectral Unmixing Using an Extended Linear Mixing Model to Address Spectral Variability. - Lucas Drumetz; Miguel Angel Veganzones; Simon Henrot; Ronald Phlypo; Jocelyn Chanussot; Christian Jutten (IEEE Trans. Image Process., 2016)

Estimating the Number of Endmembers to Use in Spectral Unmixing of Hyperspectral Data with Collaborative Sparsity. - Lucas Drumetz; Guillaume Tochon; Jocelyn Chanussot; Christian Jutten (LVA/ICA, 2017)

Improved Local Spectral Unmixing of hyperspectral data using an algorithmic regularization path for collaborative sparse regression. - Lucas Drumetz; Guillaume Tochon; Miguel Angel Veganzones; Jocelyn Chanussot; Christian Jutten (ICASSP, 2017)

Robust linear unmixing with enhanced sparsity. - Alexandre Tiard; Laurent Condat; Lucas Drumetz; Jocelyn Chanussot; Wotao Yin; Xiaoxiang Zhu 001 (ICIP, 2017)

Relationships Between Nonlinear and Space-Variant Linear Models in Hyperspectral Image Unmixing. - Lucas Drumetz; Bahram Ehsandoust; Jocelyn Chanussot; Bertrand Rivet; Massoud Babaie-Zadeh; Christian Jutten (IEEE Signal Process. Lett., 2017)

Endmembers as Directional Data for Robust Material Variability Retrieval in Hyperspectral Image Unmixing. - Lucas Drumetz; Jocelyn Chanussot; Akira Iwasaki (ICASSP, 2018)

Extended Linear Mixing Model in an Ecosytem with High Spectral Variability. - Edurne Ibarrola-Ulzurrun; Lucas Drumetz; Jocelyn Chanussot; Consuelo Gonzalo-Martín; Javier Marcello (IGARSS, 2018)

Classification Using Unmixing Models in Areas With Substantial Endmember Variability. - Edurne Ibarrola-Ulzurrun; Lucas Drumetz; Jocelyn Chanussot; Javier Marcello; Consuelo Gonzalo-Martín (WHISPERS, 2018)

Learning Differential Transport Operators for the Joint Super-Resolution of Sea Surface Tracers and Prediction of Subgrid-Scale Features. - Ronan Fablet; Julien Le Sommer; Jean-Marc Molines; Lucas Drumetz; François Rousseau 002; Bertrand Chapron (IGARSS, 2019)

Sea Surface Dynamics Reconstruction Using Neural Networks Based Kalman Filter. - Said Ouala; Ronan Fablet; Cédric Herzet; Lucas Drumetz; Bertrand Chapron; Ananda Pascual; Fabrice Collard; Lucile Gaultier (IGARSS, 2019)

Learning Ocean Dynamical Priors from Noisy Data Using Assimilation-Derived Neural Nets. - Said Ouala; Duong Nguyen; Cédric Herzet; Lucas Drumetz; Bertrand Chapron; Ananda Pascual; Fabrice Collard; Lucile Gaultier; Ronan Fablet (IGARSS, 2019)

Spatial Characterization Of Marine Vegetation Using Semisupervised Hyperspectral Unmixing. - Touria Bajjouk; Ichrak Zarati; Lucas Drumetz; Mauro Dalla Mura (WHISPERS, 2019)

EM-like Learning Chaotic Dynamics from Noisy and Partial Observations. - Duong Nguyen; Said Ouala; Lucas Drumetz; Ronan Fablet (CoRR, 2019)

Learning Latent Dynamics for Partially-Observed Chaotic Systems. - Said Ouala; Duong Nguyen; Lucas Drumetz; Bertrand Chapron; Ananda Pascual; Fabrice Collard; Lucile Gaultier; Ronan Fablet (CoRR, 2019)

End-to-end learning of energy-based representations for irregularly-sampled signals and images. - Ronan Fablet; Lucas Drumetz; François Rousseau 002 (CoRR, 2019)

Hyperspectral Classification Through Unmixing Abundance Maps Addressing Spectral Variability. - Edurne Ibarrola-Ulzurrun; Lucas Drumetz; Javier Marcello; Consuelo Gonzalo-Martín; Jocelyn Chanussot (IEEE Trans. Geosci. Remote. Sens., 2019)

Hyperspectral Image Unmixing With Endmember Bundles and Group Sparsity Inducing Mixed Norms. - Lucas Drumetz; Travis R. Meyer; Jocelyn Chanussot; Andrea L. Bertozzi; Christian Jutten (IEEE Trans. Image Process., 2019)

Learning Endmember Dynamics in Multitemporal Hyperspectral Data Using A State-Space Model Formulation. - Lucas Drumetz; Mauro Dalla Mura; Guillaume Tochon; Ronan Fablet (ICASSP, 2020)

Assimilation-Based Learning of Chaotic Dynamical Systems from Noisy and Partial Data. - Duong Nguyen; Said Ouala; Lucas Drumetz; Ronan Fablet (ICASSP, 2020)

Filtering Internal Tides from Wide-Swath Altimeter Data Using Convolutional Neural Networks. - Redouane Lguensat; Ronan Fablet; Julien Le Sommer; Sammy Metref; Emmanuel Cosme; Kaouther Ouenniche; Lucas Drumetz; Jonathan Gula (IGARSS, 2020)

Physically Informed Neural Networks for the Simulation and Data-Assimilation of Geophysical Dynamics. - Said Ouala; Ronan Fablet; Lucas Drumetz; Bertrand Chapron; Ananda Pascual; Fabrice Collard; Lucile Gaultier (IGARSS, 2020)

Joint learning of variational representations and solvers for inverse problems with partially-observed data. - Ronan Fablet; Lucas Drumetz; François Rousseau 002 (CoRR, 2020)

Learning Variational Data Assimilation Models and Solvers. - Ronan Fablet; Bertrand Chapron; Lucas Drumetz; Étienne Mémin; Olivier Pannekoucke; François Rousseau 002 (CoRR, 2020)

Variational Deep Learning for the Identification and Reconstruction of Chaotic and Stochastic Dynamical Systems from Noisy and Partial Observations. - Duong Nguyen; Said Ouala; Lucas Drumetz; Ronan Fablet (CoRR, 2020)

Residual Networks as Flows of Diffeomorphisms. - François Rousseau 002; Lucas Drumetz; Ronan Fablet (J. Math. Imaging Vis., 2020)

Spectral Unmixing: A Derivation of the Extended Linear Mixing Model From the Hapke Model. - Lucas Drumetz; Jocelyn Chanussot; Christian Jutten (IEEE Geosci. Remote. Sens. Lett., 2020)

Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean. - Elodie Martinez; Anouar Brini; Thomas Gorgues; Lucas Drumetz; Joana Roussillon; Pierre Tandeo; Guillaume Maze; Ronan Fablet (Remote. Sens., 2020)

Spectral Variability Aware Blind Hyperspectral Image Unmixing Based on Convex Geometry. - Lucas Drumetz; Jocelyn Chanussot; Christian Jutten; Wing-Kin Ma; Akira Iwasaki (IEEE Trans. Image Process., 2020)

Inferring Graph Signal Translations as Invariant Transformations for Classification Tasks. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (EUSIPCO, 2021)

Learning stochastic dynamical systems with neural networks mimicking the Euler-Maruyama scheme. - Noura Dridi; Lucas Drumetz; Ronan Fablet (EUSIPCO, 2021)

Learning Sentinel-2 Spectral Dynamics for Long-Run Predictions using Residual Neural Networks. - Joaquim Estopinan; Guillaume Tochon; Lucas Drumetz (EUSIPCO, 2021)

Geometry-Preserving Lie Group Integrators for Differential Equations on the Manifold of Symmetric Positive Definite Matrices. - Lucas Drumetz; Alexandre Reiffers-Masson; Naoufal El Bekri; Franck Vermet (GSI (2), 2021)

End-to-End Learning of Variational Models and Solvers for the Resolution of Interpolation Problems. - Ronan Fablet; Lucas Drumetz; François Rousseau 002 (ICASSP, 2021)

Improving Classification Accuracy With Graph Filtering. - Mounia Hamidouche; Carlos Lassance; Yuqing Hu 001; Lucas Drumetz; Bastien Pasdeloup; Vincent Gripon (ICIP, 2021)

End-to-End Kalman Filter for the Reconstruction of Sea Surface Dynamics from Satellite Data. - Said Ouala; Ronan Fablet; Lucas Drumetz; Bertrand Chapron; Ananda Pascual; Fabrice Collard; Lucile Gaultier (IGARSS, 2021)

Subspace Detours Meet Gromov-Wasserstein. - Clément Bonet; Titouan Vayer; Nicolas Courty; François Septier; Lucas Drumetz (Algorithms, 2021)

Graphs as Tools to Improve Deep Learning Methods. - Carlos Lassance; Myriam Bontonou; Mounia Hamidouche; Bastien Pasdeloup; Lucas Drumetz; Vincent Gripon (CoRR, 2021)

Subspace Detours Meet Gromov-Wasserstein. - Clément Bonet; Nicolas Courty; François Septier; Lucas Drumetz (CoRR, 2021)

Sliced-Wasserstein Gradient Flows. - Clément Bonet; Nicolas Courty; François Septier; Lucas Drumetz (CoRR, 2021)

Joint Interpolation and Representation Learning for Irregularly Sampled Satellite-Derived Geophysical Fields. - Ronan Fablet; Maxime Beauchamp; Lucas Drumetz; François Rousseau 002 (Frontiers Appl. Math. Stat., 2021)

Blind Hyperspectral Unmixing Based on Graph Total Variation Regularization. - Jing Qin 003; Harlin Lee; Jocelyn T. Chi; Lucas Drumetz; Jocelyn Chanussot; Yifei Lou; Andrea L. Bertozzi (IEEE Trans. Geosci. Remote. Sens., 2021)

A Local Mixup to Prevent Manifold Intrusion. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (EUSIPCO, 2022)

Preventing Manifold Intrusion with Locality: Local Mixup. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (CoRR, 2022)

Preserving Fine-Grain Feature Information in Classification via Entropic Regularization. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (CoRR, 2022)

Active Few-Shot Classification: a New Paradigm for Data-Scarce Learning Settings. - Aymane Abdali; Vincent Gripon; Lucas Drumetz; Bartosz Boguslawski (CoRR, 2022)

Correction: Martinez et al. Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean. Remote Sens. 12, 2020, 4156. - Elodie Martinez; Anouar Brini; Thomas Gorgues; Lucas Drumetz; Joana Roussillon; Pierre Tandeo; Guillaume Maze; Ronan Fablet (Remote. Sens., 2022)

Efficient Gradient Flows in Sliced-Wasserstein Space. - Clément Bonet; Nicolas Courty; François Septier; Lucas Drumetz (Trans. Mach. Learn. Res., 2022)

Learning Sentinel-2 Reflectance Dynamics for Data-Driven Assimilation and Forecasting. - Anthony Frion; Lucas Drumetz; Guillaume Tochon; Mauro Dalla Mura; Abdeldjalil Aïssa-El-Bey (EUSIPCO, 2023)

Active Learning for Efficient Few-Shot Classification. - Aymane Abdali; Vincent Gripon; Lucas Drumetz; Bartosz Boguslawski (ICASSP, 2023)

Entropy Based Feature Regularization to Improve Transferability of Deep Learning Models. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (ICASSP, 2023)

Leveraging Neural Koopman Operators to Learn Continuous Representations of Dynamical Systems from Scarce Data. - Anthony Frion; Lucas Drumetz; Mauro Dalla Mura; Guillaume Tochon; Abdeldjalil Aïssa-El-Bey (ICASSP, 2023)

Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various Dimensionalities. - Yassine El Ouahidi; Lucas Drumetz; Giulia Lioi; Nicolas Farrugia; Bastien Pasdeloup; Vincent Gripon (ICASSP, 2023)

Spherical Sliced-Wasserstein. - Clément Bonet; Paul Berg; Nicolas Courty; François Septier; Lucas Drumetz; Minh-Tan Pham (ICLR, 2023)

Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals. - Clément Bonet; Benoît Malézieux; Alain Rakotomamonjy; Lucas Drumetz; Thomas Moreau 001; Matthieu Kowalski; Nicolas Courty (ICML, 2023)

Consistency and Ambiguities of Quality No Reference Metric for Pansharpening. - Paul Aimé; Lucas Drumetz; Mauro Dalla Mura; Touria Bajjouk; René Garello (IGARSS, 2023)

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

Disambiguation of One-Shot Visual Classification Tasks: A Simplex-Based Approach. - Yassir Bendou; Lucas Drumetz; Vincent Gripon; Giulia Lioi; Bastien Pasdeloup (CoRR, 2023)

MultiHU-TD: Multifeature Hyperspectral Unmixing Based on Tensor Decomposition. - Mohamad Jouni; Mauro Dalla Mura; Lucas Drumetz; Pierre Comon (IEEE Trans. Geosci. Remote. Sens., 2023)

Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows. - Guillaume Morel; Lucas Drumetz; Simon Benaïchouche; Nicolas Courty; François Rousseau 002 (Trans. Mach. Learn. Res., 2023)

On Transfer in Classification: How Well do Subsets of Classes Generalize? - Raphaël Baena; Lucas Drumetz; Vincent Gripon (EUSIPCO, 2024)

Koopman Ensembles for Probabilistic Time Series Forecasting. - Anthony Frion; Lucas Drumetz; Guillaume Tochon; Mauro Dalla Mura; Abdeldjalil Aïssa-El-Bey (EUSIPCO, 2024)

Time Changed Normalizing Flows for Accurate SDE Modeling. - Naoufal El Bekri; Lucas Drumetz; Franck Vermet (ICASSP, 2024)

On Divergence-Free Neural ODE for Classification. - Zakaria Jarraya; Lucas Drumetz; Simon Benaïchouche; Douraied Ben Salem; François Rousseau 002 (ICPR (8), 2024)

Physics Informed and Data Driven Simulation of Underwater Images via Residual Learning. - Tanmoy Mondal; Ricardo Mendoza; Lucas Drumetz (CoRR, 2024)

Sliced-Wasserstein Distances and Flows on Cartan-Hadamard Manifolds. - Clément Bonet; Lucas Drumetz; Nicolas Courty (CoRR, 2024)

Local Mixup: Interpolation of closest input signals to prevent manifold intrusion. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (Signal Process., 2024)

Neural Koopman Prior for Data Assimilation. - Anthony Frion; Lucas Drumetz; Mauro Dalla Mura; Guillaume Tochon; Abdeldjalil Aïssa-El-Bey (IEEE Trans. Signal Process., 2024)

Land Surface Temperature Super-Resolution With a Scale-Invariance-Free Neural Approach: Application to MODIS. - Romuald Ait-Bachir; Carlos Granero-Belinchón; Aurélie Michel; Julien Michel; Xavier Briottet; Lucas Drumetz (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)

Augmented Invertible Koopman Autoencoder for long-term time series forecasting. - Anthony Frion; Lucas Drumetz; Mauro Dalla Mura; Guillaume Tochon; Abdeldjalil Aïssa-El-Bey (Trans. Mach. Learn. Res., 2025)

FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing flows and the Feynman Kac-Formula. - Naoufal El Bekri; Lucas Drumetz; Franck Vermet (CoRR, 2025)

Anomalous Samples for Few-Shot Anomaly Detection. - Aymane Abdali; Bartosz Boguslawski; Lucas Drumetz; Vincent Gripon (CoRR, 2025)

Object-Centric Cropping for Visual Few-Shot Classification. - Aymane Abdali; Bartosz Boguslawski; Lucas Drumetz; Vincent Gripon (CoRR, 2025)