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The adjoint state method is a numerical method for efficiently computing the gradient of a function or operator in a numerical optimization problem. It has applications in geophysics, seismic imaging, photonics and more recently in neural networks.
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adjoint displaystyle state equation method problem gradient optimization dual used form lambda function functional mathcal variable operator lagrangian respect mathbb
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Adjoint state method | is a | numerical method for efficiently computing the gradient of a function or operator in a numerical optimization problem | 0.90 | text |
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