The use of the Reynolds force vector in a physics informed machine learning approach for predictive turbulence modeling

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Maziar Raissi, Paris Perdikaris, George Em Karniadakis · Journal of Computational Physics · 2018 · 16.9K citations · Full text

Natural Sciences, Computer Science, Physics +16

Approximation by superpositions of a sigmoidal function

George Cybenko · Mathematics of Control Signals and Systems · 1989 · 13.7K citations

Computing, Computer Science, Machine Learning +5

The numerical computation of turbulent flows

B. E. Launder, D. B. Spalding · Computer Methods in Applied Mechanics and Engineering · 1974 · 12.7K citations

Natural Sciences, Computational Engineering, Mathematics +14

DGM: A deep learning algorithm for solving partial differential equations

Justin Sirignano, Konstantinos Spiliopoulos · Journal of Computational Physics · 2018 · 2.1K citations · Full text

Natural Sciences, Computer Science, Mathematics +13

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

Julia Ling, Andrew Kurzawski, Jeremy Alan Templeton · Journal of Fluid Mechanics · 2016 · 1.6K citations · Full text

Natural Sciences, Computer Science, Physics +17