Exact(12)
The accelerated algorithm was successfully applied to several test examples with artificial vibration data.
Based on a unique "one-iteration" paradigm, it enables accelerated algorithm development.
We propose a novel, accelerated algorithm for the approximate stochastic simulation of biochemical systems with delays.
An accelerated algorithm for the resolution of the coupled Schrödinger/Poisson system, with open boundary conditions, is presented.
This adapted number of microsteps will result in an accelerated algorithm (aFE-MD-HMM) obtaining the same accuracy of results at significantly reduced computational cost.
This paper presents the details of the proposed accelerated algorithm, having a time complexity of O(n log n), that decreases training time significantly without decreasing prediction accuracy.
Similar(48)
In this section, we compare the original algorithms and the accelerated algorithms.
The scaling of the accelerated algorithms are verified by test runs performed on a one-dimensional model.
In this paper, we propose two accelerated algorithms for finding a fixed point of a nonexpansive mapping and prove the convergence of the algorithms.
The presented procedures involve microcalorimeter measurement and calibration steps, parameters computation and systematic errors correction for both long-term and accelerated algorithms.
The present work extends existing accelerated algorithms by distributing, in a time adaptive fashion, the delayed reactions so as to minimize the computational effort while preserving their accuracy.
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