Background: Emerging evidence suggests dietary fiber may prevent cognitive decline, but its dose-response relationship and underlying mechanisms remain unclear. This study investigates the non-linear ...

Implementing exact approximations to functions. For example, by representing approximate real numbers by an interval, complex numbers by a box, p-adics by a ball, etc. From here we should have a solid ...

Abstract: Artificial neural networks (ANNs) rely significantly on activation functions for optimal performance. Traditional activation functions such as ReLU and Sigmoid are commonly used. However, ...

Two methods are discussed which result in near minimax rational approximations to the exponential function and at the same time retain the desirable property that the approximation for negative values ...

This paper presents two sets of considerations on the use of approximations to estimate freight trip generation (FTG) and freight generation (FG) rates, based on a single variable. Following recent ...

This note describes a rational approximation for the error function which has been found useful in a subroutine as an asymptotic expression of improved accuracy ...

Many types of economic problems require that we consider two variables at the same time. A typical example is the relation between price of a commodity and the demand or supply of that commodity. The ...

Implementation of the algorithm Robust Natural Actor Critic (RNAC). RNAC is introduced in our paper Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation (NeurIPS 2023).

Quantum annealing (QA) can be competitive to classical algorithms in optimizing continuous-variable functions when running on appropriate hardware, show researchers from Tokyo Tech. By comparing the ...