Neural networks in geophysical applications

By M. V. D. Baan, Christian Jutten. 2000

317 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Geophysics

View Paper: https://www.semanticscholar.org/paper/4ec8b460ba9cfa9da9c07b2ebba2a12ad438f480

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. U. Meier
2. Andrew Curtis
3. Jeannot Trampert

In Geophysics

1. Andrew Curtis
2. U. Meier
3. Jeannot Trampert
4. Andreas Fichtner
5. Jianwei Ma
6. Gregory C. Beroza
7. S. M. Mousavi
8. Fangshu Yang

Citations in the corpus

• Deep-learning tomography (2018, background): “The application of neural networks for velocity estimation and for geophysical applications in general is not new (van der Baan and Jutten, 2000).”
• Global crustal thickness from neural network inversion of surface wave data (2007, methodology): “Neural networks have been widely used in different geophysical applications, a good overview is given by van der Baan & Jutten (2000).”