JAX-DIPS: Neural bootstrapping of finite discretization methods and application to elliptic problems with discontinuities

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

Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations

Stanley Osher, James A. Sethian · Journal of Computational Physics · 1988 · 13.9K citations · Full text

Computing, Computer Science, Computational Geometry +8

A finite element method for crack growth without remeshing

Nicolas Mo�s, John E. Dolbow, Ted Belytschko · International Journal for Numerical Methods in Engineering · 1999 · 6.2K citations · Full text

Engineering, Computational Engineering, Mechanical Engineering +17

Cellular neural networks: theory

Leon O. Chua, L. Yang · IEEE Transactions on Circuits and Systems · 1988 · 4.8K citations

Engineering, Electrical Engineering, Analog Electronics +14

On the difficulty of training Recurrent Neural Networks

Razvan Pascanu, Tomáš Mikolov, Yoshua Bengio · arXiv (Cornell University) · 2012 · 3.8K citations · Full text

Computing, Computer Science, Artificial Intelligence +8