Lucas Drumetz

Orcid: 0000-0003-3362-703X

According to our database1, Lucas Drumetz authored at least 76 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Neural Koopman Prior for Data Assimilation.
IEEE Trans. Signal Process., 2024

Local Mixup: Interpolation of closest input signals to prevent manifold intrusion.
Signal Process., 2024

Sliced-Wasserstein Distances and Flows on Cartan-Hadamard Manifolds.
CoRR, 2024

Physics Informed and Data Driven Simulation of Underwater Images via Residual Learning.
CoRR, 2024

On Divergence-Free Neural ODE for Classification.
Proceedings of the Pattern Recognition - 27th International Conference, 2024

Time Changed Normalizing Flows for Accurate SDE Modeling.
Proceedings of the IEEE International Conference on Acoustics, 2024

Koopman Ensembles for Probabilistic Time Series Forecasting.
Proceedings of the 32nd European Signal Processing Conference, 2024

On Transfer in Classification: How Well do Subsets of Classes Generalize?
Proceedings of the 32nd European Signal Processing Conference, 2024

2023
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows.
Trans. Mach. Learn. Res., 2023

MultiHU-TD: Multifeature Hyperspectral Unmixing Based on Tensor Decomposition.
IEEE Trans. Geosci. Remote. Sens., 2023

Disambiguation of One-Shot Visual Classification Tasks: A Simplex-Based Approach.
CoRR, 2023

Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections.
Proceedings of the Topological, 2023

Consistency and Ambiguities of Quality No Reference Metric for Pansharpening.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals.
Proceedings of the International Conference on Machine Learning, 2023

Spherical Sliced-Wasserstein.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various Dimensionalities.
Proceedings of the IEEE International Conference on Acoustics, 2023

Leveraging Neural Koopman Operators to Learn Continuous Representations of Dynamical Systems from Scarce Data.
Proceedings of the IEEE International Conference on Acoustics, 2023

Entropy Based Feature Regularization to Improve Transferability of Deep Learning Models.
Proceedings of the IEEE International Conference on Acoustics, 2023

Active Learning for Efficient Few-Shot Classification.
Proceedings of the IEEE International Conference on Acoustics, 2023

Learning Sentinel-2 Reflectance Dynamics for Data-Driven Assimilation and Forecasting.
Proceedings of the 31st European Signal Processing Conference, 2023

2022
Efficient Gradient Flows in Sliced-Wasserstein Space.
Trans. Mach. Learn. Res., 2022

Correction: Martinez et al. Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean. Remote Sens. 12, 2020, 4156.
Remote. Sens., 2022

Active Few-Shot Classification: a New Paradigm for Data-Scarce Learning Settings.
CoRR, 2022

Preserving Fine-Grain Feature Information in Classification via Entropic Regularization.
CoRR, 2022

Preventing Manifold Intrusion with Locality: Local Mixup.
CoRR, 2022

A Local Mixup to Prevent Manifold Intrusion.
Proceedings of the 30th European Signal Processing Conference, 2022

2021
Blind Hyperspectral Unmixing Based on Graph Total Variation Regularization.
IEEE Trans. Geosci. Remote. Sens., 2021

Joint Interpolation and Representation Learning for Irregularly Sampled Satellite-Derived Geophysical Fields.
Frontiers Appl. Math. Stat., 2021

Sliced-Wasserstein Gradient Flows.
CoRR, 2021

Subspace Detours Meet Gromov-Wasserstein.
CoRR, 2021

Graphs as Tools to Improve Deep Learning Methods.
CoRR, 2021

Subspace Detours Meet Gromov-Wasserstein.
Algorithms, 2021

End-to-End Kalman Filter for the Reconstruction of Sea Surface Dynamics from Satellite Data.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

Improving Classification Accuracy With Graph Filtering.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

End-to-End Learning of Variational Models and Solvers for the Resolution of Interpolation Problems.
Proceedings of the IEEE International Conference on Acoustics, 2021

Geometry-Preserving Lie Group Integrators for Differential Equations on the Manifold of Symmetric Positive Definite Matrices.
Proceedings of the Geometric Science of Information - 6th International Conference, 2021

Learning Sentinel-2 Spectral Dynamics for Long-Run Predictions using Residual Neural Networks.
Proceedings of the 29th European Signal Processing Conference, 2021

Learning stochastic dynamical systems with neural networks mimicking the Euler-Maruyama scheme.
Proceedings of the 29th European Signal Processing Conference, 2021

Inferring Graph Signal Translations as Invariant Transformations for Classification Tasks.
Proceedings of the 29th European Signal Processing Conference, 2021

2020
Spectral Variability Aware Blind Hyperspectral Image Unmixing Based on Convex Geometry.
IEEE Trans. Image Process., 2020

Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean.
Remote. Sens., 2020

Spectral Unmixing: A Derivation of the Extended Linear Mixing Model From the Hapke Model.
IEEE Geosci. Remote. Sens. Lett., 2020

Residual Networks as Flows of Diffeomorphisms.
J. Math. Imaging Vis., 2020

Variational Deep Learning for the Identification and Reconstruction of Chaotic and Stochastic Dynamical Systems from Noisy and Partial Observations.
CoRR, 2020

Learning Variational Data Assimilation Models and Solvers.
CoRR, 2020

Joint learning of variational representations and solvers for inverse problems with partially-observed data.
CoRR, 2020

Physically Informed Neural Networks for the Simulation and Data-Assimilation of Geophysical Dynamics.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Filtering Internal Tides from Wide-Swath Altimeter Data Using Convolutional Neural Networks.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Assimilation-Based Learning of Chaotic Dynamical Systems from Noisy and Partial Data.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Learning Endmember Dynamics in Multitemporal Hyperspectral Data Using A State-Space Model Formulation.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Hyperspectral Image Unmixing With Endmember Bundles and Group Sparsity Inducing Mixed Norms.
IEEE Trans. Image Process., 2019

Hyperspectral Classification Through Unmixing Abundance Maps Addressing Spectral Variability.
IEEE Trans. Geosci. Remote. Sens., 2019

End-to-end learning of energy-based representations for irregularly-sampled signals and images.
CoRR, 2019

Learning Latent Dynamics for Partially-Observed Chaotic Systems.
CoRR, 2019

EM-like Learning Chaotic Dynamics from Noisy and Partial Observations.
CoRR, 2019

Spatial Characterization Of Marine Vegetation Using Semisupervised Hyperspectral Unmixing.
Proceedings of the 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2019

Learning Ocean Dynamical Priors from Noisy Data Using Assimilation-Derived Neural Nets.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Sea Surface Dynamics Reconstruction Using Neural Networks Based Kalman Filter.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Learning Differential Transport Operators for the Joint Super-Resolution of Sea Surface Tracers and Prediction of Subgrid-Scale Features.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2018
Classification Using Unmixing Models in Areas With Substantial Endmember Variability.
Proceedings of the 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2018

Extended Linear Mixing Model in an Ecosytem with High Spectral Variability.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Endmembers as Directional Data for Robust Material Variability Retrieval in Hyperspectral Image Unmixing.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017
Relationships Between Nonlinear and Space-Variant Linear Models in Hyperspectral Image Unmixing.
IEEE Signal Process. Lett., 2017

Robust linear unmixing with enhanced sparsity.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

Improved Local Spectral Unmixing of hyperspectral data using an algorithmic regularization path for collaborative sparse regression.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Estimating the Number of Endmembers to Use in Spectral Unmixing of Hyperspectral Data with Collaborative Sparsity.
Proceedings of the Latent Variable Analysis and Signal Separation, 2017

2016
Blind Hyperspectral Unmixing Using an Extended Linear Mixing Model to Address Spectral Variability.
IEEE Trans. Image Process., 2016

Hyperspectral Local Intrinsic Dimensionality.
IEEE Trans. Geosci. Remote. Sens., 2016

From local to global unmixing of hyperspectral images to reveal spectral variability.
Proceedings of the 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2016

Variability of the endmembers in spectral unmixing: Recent advances.
Proceedings of the 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2016

Hyperspectral unmixing with material variability using social sparsity.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

Canonical polyadic decomposition of hyperspectral patch tensors.
Proceedings of the 24th European Signal Processing Conference, 2016

2015
Semiautomatic classification of cementitious materials using scanning electron microscope images.
J. Electronic Imaging, 2015

Blind hyperspectral unmixing using an extended linear mixing model to address spectral variability.
Proceedings of the 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2015

2014
A new extended linear mixing model to address spectral variability.
Proceedings of the 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014

Binary partition tree-based local spectral unmixing.
Proceedings of the 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014


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