Revealing the predictive power of neural operators for strain evolution in digital composites

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

An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applications

Esteban Samaniego, Cosmin Anitescu, Somdatta Goswami et al. · Computer Methods in Applied Mechanics and Engineering · 2020 · 1.9K citations · Full text

Engineering, Computational Engineering, Computer Science +17

Strong, lightweight, and recoverable three-dimensional ceramic nanolattices

Lucas R. Meza, Satyajit Das, Julia R. Greer · Science · 2014 · 1.5K citations

Natural Sciences, Materials Engineering, Materials Science +17

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

Fourier Neural Operator for Parametric Partial Differential Equations

Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli et al. · arXiv (Cornell University) · 2020 · 1.1K citations · Full text

Natural Sciences, Mathematics, Physics +17