{"product_id":"machine-learning-and-artificial-intelligence-in-geosciences-hardback-9780128216699","title":"Machine Learning and Artificial Intelligence in Geosciences (Hardback) 9780128216699","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eMachine Learning and Artificial Intelligence in Geosciences\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cp\u003eContinually publishes cutting-edge reviews written by geophysics experts who cover a variety of timely topics\u003c\/p\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eBenjamin Moseley (Volume editor), Lion Krischer (Volume editor)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780128216699, Elsevier Science\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 22 September 2020\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e316 pages\u003cbr\u003e22.9 x 15.1 x 2.4 cm, 0.61 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003ci\u003eAdvances in Geophysics, Volume 61 - Machine Learning and Artificial Intelligence in Geosciences\u003c\/i\u003e, 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.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e1. Preface 2. 70 years of machine learning in geoscience in review \u003ci\u003eJesper Sören Dramsch \u003c\/i\u003e3. Machine learning and fault rupture: A review \u003ci\u003eChristopher X. Ren, Claudia Hulbert, Paul A. Johnson and Bertrand Rouet-Leduc \u003c\/i\u003e4. Machine learning techniques for fractured media \u003ci\u003eShriram Srinivasan \u003c\/i\u003e5. Seismic signal augmentation to improve generalization of deep neural networks \u003ci\u003eWeiqiang Zhu , S. Mostafa Mousavi and Gregory C. Beroza \u003c\/i\u003e6. Deep generator priors for Bayesian seismic inversion \u003ci\u003eZhilong Fang, Hongjian Fang and L. Demanet \u003c\/i\u003e7. An introduction to the two-scale homogenization method for seismology \u003ci\u003eYann Capdeville, Paul Cupillard and Sneha Singh\u003c\/i\u003e\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: The environment [\u003ca title=\"See our other books on The environment\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22The%20environment%20%5BRN%5D%22\"\u003eRN\u003c\/a\u003e], Geology \u0026amp; the lithosphere [\u003ca title=\"See our other books on Geology \u0026amp; the lithosphere\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Geology%20\u0026amp;%20the%20lithosphere%20%5BRBG%5D%22\"\u003eRBG\u003c\/a\u003e], Geophysics [\u003ca title=\"See our other books on Geophysics\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Geophysics%20%5BPHVG%5D%22\"\u003ePHVG\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Academic Press","offers":[{"title":"Default Title","offer_id":46650275168536,"sku":"9780128216699","price":149.45,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/products\/9780128216699.jpg?v=1694107217","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/machine-learning-and-artificial-intelligence-in-geosciences-hardback-9780128216699","provider":"Freshly Printed Books","version":"1.0","type":"link"}