GD
Geodynamics

Denise Degen

Denise Degen is a Postdoctoral researcher at the RWTH Aachen University (Germany) within the group of Computational Geoscience, Geothermics, and Reservoir Geophysics. Her research interests focus on surrogate model construction (including methods as physics-based machine learning and model order reduction) for applications such as geothermal energy and geodynamics. Follow her on Research Gate (https://www.researchgate.net/profile/Denise-Degen) for the latest updates on her research or write an email to denise.degen@cgre.rwth-aachen.de.

Physics-Based Machine Learning – Curse or Blessing?

and August 16, 2023
Physics-Based Machine Learning – Curse or Blessing?
AI-generated Earth (created with craiyon.com)

The advance of Artificial Intelligence is impacting all spheres of human activity, and Geosciences are no exception. In this week’s post, Denise Degen from RWTH Aachen University, Germany, gives us a glimpse of what this means for Geodynamics. Discussing the advantages and caveats of different approaches, she shows how physics-based Machine Learning may help us investigating and understanding comp ...[Read More]