A transfer learning-physics informed neural network (TL-PINN) for vortex-induced vibration

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

A Comprehensive Survey on Transfer Learning

Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan et al. · Proceedings of the IEEE · 2020 · 6.2K citations

Computing, Computer Science, Knowledge Transfer +5

A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics

Ehsan Haghighat, Maziar Raissi, Adrian Moure et al. · Computer Methods in Applied Mechanics and Engineering · 2021 · 1.2K citations

Engineering, Computational Engineering, Physics +16

Emerging artificial intelligence methods in structural engineering

Hadi Salehi, Rigoberto Burgueño · Engineering Structures · 2018 · 1K citations

Engineering, Civil Engineering, Computational Engineering +14

Numerical study and physical analysis of the pressure and velocity fields in the near wake of a circular cylinder

Marianna Braza, P. Chassaing, H. Ha Minh · Journal of Fluid Mechanics · 1986 · 822 citations

Engineering, Mechanical Engineering, Physics +17