Rapid seismic domain transfer: Seismic velocity inversion and modeling using deep generative neural networks. - Lukas Mosser; Wouter Kimman; Jesper Sören Dramsch; Steve Purves; Alfredo De la Fuente; Graham Ganssle (CoRR, 2018)

Including Physics in Deep Learning - An example from 4D seismic pressure saturation inversion. - Jesper Sören Dramsch; Gustavo Corte; Hamed Amini; Colin MacBeth; Mikael Lüthje (CoRR, 2019)

70 years of machine learning in geoscience in review. - Jesper Sören Dramsch (CoRR, 2020)

Complex-valued neural networks for machine learning on non-stationary physical data. - Jesper Sören Dramsch; Mikael Lüthje; Anders Nymark Christensen (Comput. Geosci., 2021)

Bayesian Convolutional Neural Networks for Seismic Facies Classification. - Runhai Feng; Niels Balling; Dario Grana; Jesper Sören Dramsch; Thomas Mejer Hansen (IEEE Trans. Geosci. Remote. Sens., 2021)

Deep Unsupervised 4-D Seismic 3-D Time-Shift Estimation With Convolutional Neural Networks. - Jesper Sören Dramsch; Anders Nymark Christensen; Colin MacBeth; Mikael Lüthje (IEEE Trans. Geosci. Remote. Sens., 2022)

Regional data-driven weather modeling with a global stretched-grid. - Thomas Nils Nipen; Håvard Homleid Haugen; Magnus Sikora Ingstad; Even Marius Nordhagen; Aram Farhad Shafiq Salihi; Paulina Tedesco; Ivar Ambjørn Seierstad; Jørn Kristiansen; Simon Lang; Mihai Alexe; Jesper Sören Dramsch; Baudouin Raoult; et al. (CoRR, 2024)

Robustness of AI-based weather forecasts in a changing climate. - Thomas Rackow; Nikolay Koldunov; Christian Lessig; Irina Sandu; Mihai Alexe; Matthew Chantry; Mariana Clare; Jesper Sören Dramsch; Florian Pappenberger; Xabier Pedruzo-Bagazgoitia; Steffen Tietsche; Thomas Jung (CoRR, 2024)