365 citations · 913 across the 4 of their papers we have counts for
4 papers
Improving prediction of the terrestrial water storage anomalies during the GRACE and GRACE-FO gap with Bayesian convolutional neural networks
Shaoxing Mo, Yulong Zhong, Xiaoqing Shi +3
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 a…
Integration of adversarial autoencoders with residual dense convolutional networks for estimation of non-Gaussian hydraulic conductivities
Shaoxing Mo, Nicholas Zabaras, Xiaoqing Shi +1
Inverse modeling for the estimation of non-Gaussian hydraulic conductivity fields in subsurface flow and solute transport models remains a challenging problem. This is mainly due t…
Deep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identification
Shaoxing Mo, Nicholas Zabaras, Xiaoqing Shi +1
Identification of a groundwater contaminant source simultaneously with the hydraulic conductivity in highly-heterogeneous media often results in a high-dimensional inverse problem.…
Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media
Shaoxing Mo, Yinhao Zhu, Nicholas Zabaras +2
Surrogate strategies are used widely for uncertainty quantification of groundwater models in order to improve computational efficiency. However, their application to dynamic multip…