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- In applied mathematics, Hessian automatic differentiation are techniques based on automatic differentiation (AD)that calculate the second derivative of an -dimensional function, known as the Hessian matrix. When examining a function in a neighborhood of a point, one can discard many complicated global aspects of the function and accurately approximate it with simpler functions. The quadratic approximation is the best-fitting quadratic in the neighborhood of a point, and is frequently used in engineering and science. To calculate the quadratic approximation, one must first calculate its gradient and Hessian matrix. Let , for each the Hessian matrix is the second order derivative and is a symmetric matrix. (en)
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- In applied mathematics, Hessian automatic differentiation are techniques based on automatic differentiation (AD)that calculate the second derivative of an -dimensional function, known as the Hessian matrix. Let , for each the Hessian matrix is the second order derivative and is a symmetric matrix. (en)
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- Hessian automatic differentiation (en)
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