260 citations · 657 across the 30 of their papers we have counts for
6 papers · 1 filter
MultiHU-TD: Multifeature Hyperspectral Unmixing Based on Tensor Decomposition
Mohamad Jouni, Mauro Dalla Mura, Lucas Drumetz +1
Hyperspectral unmixing allows representing mixed pixels as a set of pure materials weighted by their abundances. Spectral features alone are often insufficient, so it is common to…
Neural Koopman prior for data assimilation
Anthony Frion, Lucas Drumetz, Mauro Dalla Mura +2
With the increasing availability of large scale datasets, computational power and tools like automatic differentiation and expressive neural network architectures, sequential data…
Learning Sentinel-2 reflectance dynamics for data-driven assimilation and forecasting
Anthony Frion, Lucas Drumetz, Guillaume Tochon +2
Over the last few years, massive amounts of satellite multispectral and hyperspectral images covering the Earth's surface have been made publicly available for scientific purpose,…
Leveraging Neural Koopman Operators to Learn Continuous Representations of Dynamical Systems from Scarce Data
Anthony Frion, Lucas Drumetz, Mauro Dalla Mura +2
Over the last few years, several works have proposed deep learning architectures to learn dynamical systems from observation data with no or little knowledge of the underlying phys…
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals
Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy +4
When dealing with electro or magnetoencephalography records, many supervised prediction tasks are solved by working with covariance matrices to summarize the signals. Learning with…
Disambiguation of One-Shot Visual Classification Tasks: A Simplex-Based Approach
Yassir Bendou, Lucas Drumetz, Vincent Gripon +2
The field of visual few-shot classification aims at transferring the state-of-the-art performance of deep learning visual systems onto tasks where only a very limited number of tra…