A Review of Physics-based Machine Learning in Civil Engineering

9 October 2021

Papers citing "A Review of Physics-based Machine Learning in Civil Engineering"

28 / 28 papers shown

Title
Predicting the spread of COVID-19 in Delhi, India using Deep Residual Recurrent Neural Networks S. Vadyala S. N. Betgeri 65 2 0 09 Oct 2021
Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows Hamidreza Eivazi S. L. C. Martínez S. Hoyas Ricardo Vinuesa 58 94 0 03 Sep 2021
Natural Language Processing Accurately Categorizes Indications, Findings and Pathology Reports from Multicenter Colonoscopy S. Vadyala E. Sherer 24 8 0 25 Aug 2021
Enhancing predictive skills in physically-consistent way: Physics Informed Machine Learning for Hydrological Processes Pravin Bhasme Jenil Vagadiya Udit Bhatia AI4CE 25 66 0 22 Apr 2021
Physics-Informed Neural Network Method for Solving One-Dimensional Advection Equation Using PyTorch S. Vadyala S. N. Betgeri PINN 50 26 0 15 Mar 2021
Physics Guided Machine Learning Methods for Hydrology A. Khandelwal Shaoming Xu Xiang Li X. Jia M. Steinbach C. Duffy John L. Nieber Vipin Kumar AI4CE 38 38 0 02 Dec 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 468 2,384 0 18 Oct 2020
Machine learning for metal additive manufacturing: Predicting temperature and melt pool fluid dynamics using physics-informed neural networks Qiming Zhu Zeliang Liu Jinhui Yan PINN AI4CE 40 301 0 28 Jul 2020
Convolutional-network models to predict wall-bounded turbulence from wall quantities L. Guastoni A. Güemes A. Ianiro S. Discetti P. Schlatter Hossein Azizpour R. Vinuesa 39 168 0 22 Jun 2020
Understanding and mitigating gradient pathologies in physics-informed neural networks Sizhuang He Yujun Teng P. Perdikaris AI4CE PINN 89 293 0 13 Jan 2020
Deep Network Approximation for Smooth Functions Jianfeng Lu Zuowei Shen Haizhao Yang Shijun Zhang 97 247 0 09 Jan 2020
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN 86 271 0 26 Sep 2019
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs Xuhui Meng Zhen Li Dongkun Zhang George Karniadakis PINN AI4CE 56 450 0 23 Sep 2019
Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods Ferdinando Fioretto Terrence W.K. Mak Pascal Van Hentenryck AI4CE 119 202 0 19 Sep 2019
Modeling the Dynamics of PDE Systems with Physics-Constrained Deep Auto-Regressive Networks N. Geneva N. Zabaras AI4CE 59 273 0 13 Jun 2019
Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction N. Benjamin Erichson Michael Muehlebach Michael W. Mahoney AI4CE PINN 56 141 0 26 May 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 92 866 0 18 Jan 2019
Deep Learning of Vortex Induced Vibrations M. Raissi Zhicheng Wang M. Triantafyllou George Karniadakis AI4CE 58 376 0 26 Aug 2018
HybridNet: Integrating Model-based and Data-driven Learning to Predict Evolution of Dynamical Systems Yun Long Xueyuan She Saibal Mukhopadhyay 44 58 0 19 Jun 2018
Deep Fluids: A Generative Network for Parameterized Fluid Simulations Byungsoo Kim Vinicius Azevedo N. Thürey Theodore Kim Markus Gross B. Solenthaler GAN 52 389 0 06 Jun 2018
JUNIPR: a Framework for Unsupervised Machine Learning in Particle Physics Anders Andreassen Ilya Feige Christopher Frye M. Schwartz MU 63 137 0 25 Apr 2018
Optimal approximation of continuous functions by very deep ReLU networks Dmitry Yarotsky 168 293 0 10 Feb 2018
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification Rohit Tripathy Ilias Bilionis AI4CE 58 406 0 02 Feb 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations M. Raissi PINN AI4CE 112 752 0 20 Jan 2018
A unified deep artificial neural network approach to partial differential equations in complex geometries Jens Berg K. Nystrom AI4CE 58 586 0 17 Nov 2017
The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems E. Weinan Ting Yu 115 1,380 0 30 Sep 2017
Machine Learning of Linear Differential Equations using Gaussian Processes M. Raissi George Karniadakis 77 550 0 10 Jan 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 51 981 0 27 Dec 2016