Bridging the gap between GRACE and GRACE-FO missions with deep learning aided water storage simulations-Reference-Cited by-同舟云学术

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Bridging the gap between GRACE and GRACE-FO missions with deep learning aided water storage simulations

Published:2022-07 Issue: Volume:830 Page:154701
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Uz Metehan,Atman Kazım Gökhan,Akyilmaz Orhan,Shum C.K.,Keleş Merve,Ay Tuğçe,Tandoğdu Bihter,Zhang Yu,Mercan Hüseyin

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference77 articles.

1. TensorFlow: A System for Large-Scale Machine Learning. 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16);Abadi,2016

2. Machine Learning Applications for Downscaling Groundwater Storage Changes Integrating Satellite Gravimetry and Other Observations;Agarwal,2020

3. Understanding the unusual 2017 monsoon and floods in South Asia;Akanda,2017

4. What regularized auto-encoders learn from the data-generating distribution the;Alain;J. Mach. Learn. Res.,2014

5. GRACE accelerometer data transplant;Bandikova;Adv. Space Res.,2019

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