Form-finding of tensile membrane structures with strut and anchorage supports using physics-informed machine learning

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

The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems

E Weinan, Bing Yu · Communications in Mathematics and Statistics · 2018 · 1.3K citations

Natural Sciences, Computer Science, Mathematics +13

Machine learning–enabled high-entropy alloy discovery

Ziyuan Rao, Po‐Yen Tung, Ruiwen Xie et al. · Science · 2022 · 668 citations

Natural Sciences, Materials Engineering, Materials Science +17

Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems

Jeremy Yu, Lu Lu, Xuhui Meng et al. · Computer Methods in Applied Mechanics and Engineering · 2022 · 634 citations · Full text

Natural Sciences, Mathematics, Physics +14