1 code implementation • 18 Dec 2019 • Arthur Pajot, Emmanuel de Bezenac, Patrick Gallinari
This allows us sampling from the latent component in order to generate a distribution of images associated to an observation.
no code implementations • 25 Sep 2019 • Yuan Yin, Arthur Pajot, Emmanuel de Bézenac, Patrick Gallinari
We tackle the problem of inpainting occluded area in spatiotemporal sequences, such as cloud occluded satellite observations, in an unsupervised manner.
no code implementations • ICLR 2019 • Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari
Spatio-Temporal processes bear a central importance in many applied scientific fields.
1 code implementation • ICLR 2019 • Arthur Pajot, Emmanuel de Bezenac, Patrick Gallinari
We address the problem of recovering an underlying signal from lossy, inaccurate observations in an unsupervised setting.
no code implementations • 26 Feb 2019 • Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Julien Brajard, Patrick Gallinari
We consider the problem of forecasting complex, nonlinear space-time processes when observations provide only partial information of on the system's state.
2 code implementations • ICLR 2018 • Emmanuel de Bezenac, Arthur Pajot, Patrick Gallinari
We consider the use of Deep Learning methods for modeling complex phenomena like those occurring in natural physical processes.