4 papers · 1 filter
Uncertainty-aware data assimilation through variational inference
Anthony Frion, David S Greenberg
Data assimilation, consisting in the combination of a dynamical model with a set of noisy and incomplete observations in order to infer the state of a system over time, involves un…
Augmented Invertible Koopman Autoencoder for long-term time series forecasting
Anthony Frion, Lucas Drumetz, Mauro Dalla Mura +2
Following the introduction of Dynamic Mode Decomposition and its numerous extensions, many neural autoencoder-based implementations of the Koopman operator have recently been propo…
Koopman Ensembles for Probabilistic Time Series Forecasting
Anthony Frion, Lucas Drumetz, Guillaume Tochon +2
In the context of an increasing popularity of data-driven models to represent dynamical systems, many machine learning-based implementations of the Koopman operator have recently b…
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…