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stat.ML2019
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
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
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…