Machine learning in geosciences / edited by Ben Moseley, Lion Krischer.

First edition.

Amsterdam, The Netherlands : Elsevier Academic Press, 2020.

©2020.

1 online resource (x, 306 pages) : illustrations (some colour).

Access is available to the Yale community.

Description based on online resource; title from publisher's web page (ScienceDirect, viewed October 12, 2020)

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"Advances in Geophysics, Volume 61 - Machine Learning and Artificial Intelligence in Geosciences, the latest release in this highly-respected publication in the field of geophysics, contains new chapters on a variety of topics, including a historical review on the development of machine learning, machine learning to investigate fault rupture on various scales, a review on machine learning techniques to describe fractured media, signal augmentation to improve the generalization of deep neural networks, deep generator priors for Bayesian seismic inversion, as well as a review on homogenization for seismology, and more."--publisher's web page, viewed October 12, 2020.

Elsevier ScienceDirect All Books. OCLC KB.

Print version Machine learning in geosciences First edition Elsevier Academic Press, 2020

Books / Online

English

August 06, 2021

Includes bibliographical references.

Electronic books