Integration of knowledge and data in machine learning

15 February 2022

Papers citing "Integration of knowledge and data in machine learning"

25 / 25 papers shown

Title
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning Chengping Rao Pu Ren Yang Liu Hao Sun AI4CE 85 29 0 28 Jan 2022
Discovering PDEs from Multiple Experiments Georges Tod G. Both R. Kusters 111 1 0 24 Sep 2021
Any equation is a forest: Symbolic genetic algorithm for discovering open-form partial differential equations (SGA-PDE) Yuntian Chen Yingtao Luo Qiang Liu Hao Xu Dongxiao Zhang AI4CE 58 57 0 09 Jun 2021
Robust discovery of partial differential equations in complex situations Hao Xu Dongxiao Zhang AI4CE 54 29 0 31 May 2021
Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method Yuntian Chen Dou Huang Dongxiao Zhang Junsheng Zeng Nanzhe Wang Haoran Zhang Jinyue Yan PINN 64 109 0 11 Dec 2020
Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data Hao Xu Dongxiao Zhang Nanzhe Wang 70 34 0 24 Nov 2020
Deep-learning of Parametric Partial Differential Equations from Sparse and Noisy Data Hao Xu Dongxiao Zhang Junsheng Zeng 54 57 0 16 May 2020
Physics-informed learning of governing equations from scarce data Zhao Chen Yang Liu Hao Sun PINN AI4CE 60 393 0 05 May 2020
Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network Nanzhe Wang Haibin Chang Dongxiao Zhang 46 59 0 25 Apr 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 47 89 0 21 Jan 2020
Deep Learning of Subsurface Flow via Theory-guided Neural Network Nanzhe Wang Dongxiao Zhang Haibin Chang Heng Li AI4CE 70 228 0 24 Oct 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 229 2,119 0 08 Oct 2019
Data-driven PDE discovery with evolutionary approach M. Maslyaev A. Hvatov Anna V. Kaluzhnaya 46 25 0 19 Mar 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 92 867 0 18 Jan 2019
PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network Zichao Long Yiping Lu Bin Dong AI4CE 72 552 0 30 Nov 2018
Identification of physical processes via combined data-driven and data-assimilation methods Haibin Chang Dongxiao Zhang 32 32 0 29 Oct 2018
Learning Equations for Extrapolation and Control Subham S. Sahoo Christoph H. Lampert Georg Martius 43 233 0 19 Jun 2018
Reinforcement Learning of Theorem Proving C. Kaliszyk Josef Urban Henryk Michalewski Miroslav Olsák 34 148 0 19 May 2018
Saliency Preservation in Low-Resolution Grayscale Images Shivanthan A. C. Yohanandan A. Dyer Dacheng Tao A. Song FAtt 66 24 0 06 Dec 2017
Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling Arka Daw Anuj Karpatne William Watkins J. Read Vipin Kumar PINN 38 533 0 31 Oct 2017
PDE-Net: Learning PDEs from Data Zichao Long Yiping Lu Xianzhong Ma Bin Dong DiffM AI4CE 38 755 0 26 Oct 2017
Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data Anuj Karpatne G. Atluri James H. Faghmous M. Steinbach A. Banerjee A. Ganguly Shashi Shekhar N. Samatova Vipin Kumar AI4CE 53 983 0 27 Dec 2016
Constrained Convolutional Neural Networks for Weakly Supervised Segmentation Deepak Pathak Philipp Krahenbuhl Trevor Darrell SSeg 85 613 0 11 Jun 2015
Two-Stream Convolutional Networks for Action Recognition in Videos Karen Simonyan Andrew Zisserman 242 7,535 0 09 Jun 2014
Distributed Representations of Sentences and Documents Quoc V. Le Tomas Mikolov FaML 251 9,239 0 16 May 2014