Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The development of machine learning interatomic potentials (MLIPs) has revolutionized ...

fisher information is used as the proxy of uncertainty. The larger the fisher information is, the larger the Hessian matrix is, the greater the uncertainty will be. The feeling is counterintuitive: ...

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 ...

I would like to ask about line 61 in your gptq.py file: inp = math.sqrt(2 / self.nsamples) * inp.float(). According to the paper, it seems that it should be written as follows: inp = math.sqrt(tmp / ...

Abstract: In this paper, a Hessian matrix based multi-focus image fusion method is proposed. First, the integral map is introduced for fast compute the Hessian matrix of source images at different ...

The town of Empty Interior, NY was a place of spell-bound mathematics. Fantastical concepts like infinities acting the same as other numbers, or horrifying ones like a curse to fail every math exam ...

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