Physics-Informed Neural Networks with Hard Constraints for Inverse Design

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 Limited Memory Algorithm for Bound Constrained Optimization

Richard H. Byrd, Peihuang Lu, Jorge Nocedal et al. · SIAM Journal on Scientific Computing · 1995 · 6.2K citations

Natural Sciences, Computer Science, Mathematics +16

Topology optimization approaches

Ole Sigmund, Kurt Maute · Structural and Multidisciplinary Optimization · 2013 · 2.8K citations

Artificial neural networks for solving ordinary and partial differential equations

IEEE Transactions on Neural Networks · 1998 · 2.2K citations · Full text

Natural Sciences, Computational Engineering, Computer Science +17

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

Maziar Raissi, Alireza Yazdani, George Em Karniadakis · Science · 2020 · 2K citations · Full text

Computing, Computer Science, Physics +16