Search Results for author:
Found 2 papers, 0 papers with code
SPDE priors for uncertainty quantification of end-to-end neural data assimilation schemes
Recent advances in the deep learning community also enables to adress this problem as neural architecture embedding data assimilation variational framework.
A stable deep adversarial learning approach for geological facies generation
In this paper, we review the generative deep learning approaches, in particular the adversarial ones and the stabilization techniques that aim to facilitate their training.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
