Construct · 1 fields · 1 citations

physics-informed neural network: a standalone construct

One name. One construct. A landmark on the map.

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Machine learning

a neural network trained to fit data while also satisfying known partial differential equations, which enter the loss as penalty terms.

In machine learning, physics-informed neural network refers to a neural network trained to fit data while also satisfying known partial differential equations, which enter the loss as penalty terms. This meaning comes from Raissi (2019) in Journal of Computational Physics.[1]

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Nearby constructs

learning6 fields · 14 citationsjingle · one name, six constructs loss2 fields · 3 citationsjingle · one word, two constructs network4 fields · 6 citationsjingle · one word, four constructs

References

Raissi, M., Perdikaris, P., & Karniadakis, G. E. (2019). Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. Journal of Computational Physics, 378, 686-707. https://doi.org/10.1016/j.jcp.2018.10.045

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