no code implementations • 21 Jan 2021 • Shaoxing Mo, Yulong Zhong, Xiaoqing Shi, Wei Feng, Xin Yin, Jichun Wu
The Gravity Recovery and Climate Experiment (GRACE) satellite and its successor GRACE Follow-On (GRACE-FO) provide valuable and accurate observations of terrestrial water storage anomalies (TWSAs) at a global scale.
1 code implementation • 26 Jun 2019 • Shaoxing Mo, Nicholas Zabaras, Xiaoqing Shi, Jichun Wu
In addition, a deep residual dense convolutional network (DRDCN) is proposed for surrogate modeling of forward models with high-dimensional and highly-complex mappings.
1 code implementation • 22 Dec 2018 • Shaoxing Mo, Nicholas Zabaras, Xiaoqing Shi, Jichun Wu
Results indicate that, with relatively limited training data, the deep autoregressive neural network consisting of 27 convolutional layers is capable of providing an accurate approximation for the high-dimensional model input-output relationship.
1 code implementation • 2 Jul 2018 • Shaoxing Mo, Yinhao Zhu, Nicholas Zabaras, Xiaoqing Shi, Jichun Wu
A training strategy combining a regression loss and a segmentation loss is proposed in order to better approximate the discontinuous saturation field.