Integrating Machine Learning with Physics-Based Modeling

Integrating Machine Learning with Physics-Based Modeling

4 June 2020

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Papers citing "Integrating Machine Learning with Physics-Based Modeling"

11 / 11 papers shown

Title
Structure-preserving neural networks for the regularized entropy-based closure of the Boltzmann moment system Steffen Schotthöfer M. P. Laiu Martin Frank C. Hauck 77 1 0 22 Apr 2024
Knowledge-augmented Deep Learning and Its Applications: A Survey Zijun Cui Tian Gao Kartik Talamadupula Qiang Ji 112 20 0 30 Nov 2022
Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models Naoya Takeishi Alexandros Kalousis AAML 94 3 0 24 Oct 2022
Multiway Ensemble Kalman Filter Yu Wang Alfred Hero 56 1 0 08 Dec 2021
Randomized multilevel Monte Carlo for embarrassingly parallel inference Ajay Jasra K. Law Alexander Tarakanov Fangyuan Yu 85 2 0 05 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 125 69 0 02 Jul 2021
Polyconvex anisotropic hyperelasticity with neural networks Dominik K. Klein Mauricio Fernández Robert J. Martin P. Neff Oliver Weeger 88 157 0 20 Jun 2021
Frame-independent vector-cloud neural network for nonlocal constitutive modeling on arbitrary grids Xueqing Zhou Jiequn Han Heng Xiao 80 31 0 11 Mar 2021
APIK: Active Physics-Informed Kriging Model with Partial Differential Equations Jialei Chen Zhehui Chen Chuck Zhang C. F. J. Wu 99 15 0 22 Dec 2020
Learning Thermodynamically Stable and Galilean Invariant Partial Differential Equations for Non-equilibrium Flows Juntao Huang Zhiting Ma Y. Zhou W. Yong AI4CE 63 16 0 28 Sep 2020
Machine Learning and Computational Mathematics Weinan E PINN AI4CE 88 62 0 23 Sep 2020