Machine learning based dual flat-spherical indentation approach for rough metallic surfaces

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

Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next

Salvatore Cuomo, Vincenzo Schiano Di Cola, Fabio Giampaolo et al. · Journal of Scientific Computing · 2022 · 2.3K citations · Full text

Computing, Computer Science, Physics +16

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

Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data

Luning Sun, Han Gao, Shaowu Pan et al. · Computer Methods in Applied Mechanics and Engineering · 2019 · 982 citations · Full text

Computing, Computational Engineering, Physics +12

Extraction of mechanical properties of materials through deep learning from instrumented indentation

Lu Lu, Ming Dao, Punit Kumar et al. · Proceedings of the National Academy of Sciences · 2020 · 344 citations · Full text

Natural Sciences, Materials Engineering, Materials Science +17