4 papers
Variational Augmented Invertible Koopman Autoencoder for probabilistic time series forecasting
Anthony Frion, Lucas Drumetz, Guillaume Tochon +3
Neural Koopman autoencoder models have been shown to successfully build a latent embedding with linear dynamics for arbitrary dynamical systems, enabling strong performance in long…
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…