3 citations · 3 across the 1 of their papers we have counts for
2 papers
cs.LG2019
Complex-valued neural networks for machine learning on non-stationary physical data
Jesper Sören Dramsch, Mikael Lüthje, Anders Nymark Christensen
Deep learning has become an area of interest in most scientific areas, including physical sciences. Modern networks apply real-valued transformations on the data. Particularly, con…
physics.geo-ph2019★ 3 cited
Including Physics in Deep Learning -- An example from 4D seismic pressure saturation inversion
Jesper Sören Dramsch, Gustavo Corte, Hamed Amini +2
Geoscience data often have to rely on strong priors in the face of uncertainty. Additionally, we often try to detect or model anomalous sparse data that can appear as an outlier in…