Lecture 5 Part 1: Derivative of Matrix Determinant and Inverse

Name: Lecture 5 Part 1: Derivative of Matrix Determinant and Inverse
Uploaded: 2023-12-01T16:23:26Z
Duration: 28 min 3 s
Description: Description: The first ~6 minutes are on the topic Norms and Derivatives: Why a norm of the input and output are needed to define a derivative. Now we can find the “matrix gradient” of the determinant function (leading to the “adjugate” matrix), and the “Jacobian” of a matrix inverse. Instructors: Alan Edelman, Steven G. Johnson

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Lecture 5 Part 2: Forward Automatic Differentiation via Dual Numbers

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Description: The first ~6 minutes are on the topic Norms and Derivatives: Why a norm of the input and output are needed to define a derivative. Now we can find the “matrix gradient” of the determinant function (leading to the “adjugate” matrix), and the “Jacobian” of a matrix inverse.

Instructors: Alan Edelman, Steven G. Johnson