Combining Physically-Based Modeling and Deep Learning for Fusing GRACE Satellite Data: Can We Learn from Mismatch?

31 January 2019

Papers citing "Combining Physically-Based Modeling and Deep Learning for Fusing GRACE Satellite Data: Can We Learn from Mismatch?"

4 / 4 papers shown

Title
Applications of physics-informed scientific machine learning in subsurface science: A survey A. Sun H. Yoon C. Shih Zhi Zhong AI4CE 82 11 0 10 Apr 2021
Improving prediction of the terrestrial water storage anomalies during the GRACE and GRACE-FO gap with Bayesian convolutional neural networks S. Mo Yulong Zhong Xiaoqing Shi W. Feng Xin Yin Jichun Wu AI4Cl 26 67 0 21 Jan 2021
A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources M. Sit B. Demiray Z. Xiang Gregory Ewing Y. Sermet Ibrahim Demir AI4Cl AI4CE 86 333 0 17 Jun 2020
70 years of machine learning in geoscience in review Jesper Sören Dramsch VLM AI4CE 111 163 0 16 Jun 2020