Abstract: The Hessian matrix conveys important information about the curvature, spectrum and partial derivatives of a function, and is required in a variety of tasks. However, computing the exact ...

Hessian matrices are square matrices consisting of all possible combinations of second partial derivatives of a scalar-valued initial function. As such, Hessian matrices may be treated as elementary ...

Hessian matrix is a square matrix of second-order partial derivative of a scalar-valued function. In the context of neural networks and deep learning, this function typically represents the loss or ...

Hi, there. Thanks for making this great repo public. I'm using Pinocchio to compute the partial derivatives of the Jacobian matrix with respect to q, a.k.a. dJ/dq. I have been calculating the Hessian ...

Abstract: Prestack inversion is typically based on the Zoeppritz equation combined with gradient-based optimization of objective functions. To address the limitations of traditional gradient-based ...