Identification of physical processes via combined data-driven and data-assimilation methods

29 October 2018

Papers citing "Identification of physical processes via combined data-driven and data-assimilation methods"

11 / 11 papers shown

Title
Finite Expression Methods for Discovering Physical Laws from Data Zhongyi Jiang Chunmei Wang Haizhao Yang 66 7 0 15 May 2023
Identification of Physical Processes and Unknown Parameters of 3D Groundwater Contaminant Problems via Theory-guided U-net Tianhao He Haibin Chang Dongxiao Zhang PINN AI4CE 72 0 0 30 Apr 2022
Discovering Governing Equations by Machine Learning implemented with Invariance Chao Chen Xiaowei Jin Hui Li PINN AI4CE 39 1 0 29 Mar 2022
Integration of knowledge and data in machine learning Yuntian Chen Dongxiao Zhang PINN 88 33 0 15 Feb 2022
Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data Hao Xu Dongxiao Zhang Nanzhe Wang 82 34 0 24 Nov 2020
Data-driven Identification of 2D Partial Differential Equations using extracted physical features Kazem Meidani A. Farimani 54 17 0 20 Oct 2020
Deep-learning of Parametric Partial Differential Equations from Sparse and Noisy Data Hao Xu Dongxiao Zhang Junsheng Zeng 70 57 0 16 May 2020
DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm Hao Xu Haibin Chang Dongxiao Zhang AI4CE 65 89 0 21 Jan 2020
Coercing Machine Learning to Output Physically Accurate Results Z. Geng Dan Johnson Ronald Fedkiw 3DH 46 37 0 21 Oct 2019
DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data Hao Xu Haibin Chang Dongxiao Zhang AI4CE 63 70 0 13 Aug 2019
PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network Zichao Long Yiping Lu Bin Dong AI4CE 89 553 0 30 Nov 2018