329 citations · 1.7k across the 32 of their papers we have counts for
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stat.ML2019★ 57 cited
Ensemble Neural Networks (ENN): A gradient-free stochastic method
Yuntian Chen, Haibin Chang, Meng Jin +1
In this study, an efficient stochastic gradient-free method, the ensemble neural networks (ENN), is developed. In the ENN, the optimization process relies on covariance matrices ra…
stat.ML2019★ 36 cited
DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data
Hao Xu, Haibin Chang, Dongxiao Zhang
In recent years, data-driven methods have been developed to learn dynamical systems and partial differential equations (PDE). The goal of such work is discovering unknown physics a…
stat.ML2018★ 35 cited
Identification of physical processes via combined data-driven and data-assimilation methods
Haibin Chang, Dongxiao Zhang
With the advent of modern data collection and storage technologies, data-driven approaches have been developed for discovering the governing partial differential equations (PDE) of…