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加性多指标高斯过程及其在夸克—胶子等离子体多物理代理建模中的应用AI 解读

The Quark-Gluon Plasma (QGP) is a unique phase of nuclear matter, theorized to have filled the Universe shortly after the Big Bang. A critical challenge in studying the QGP is that, to reconcile experimental observables with theoretical parameters, one requires many simulation runs of a complex physics model over a high-dimensional parameter space. Each run is computationally expensive, requiring thousands of CPU hours, thus limiting physicists to only several hundred runs.…

用于贝叶斯优化的层级期望改进方法AI 解读

The Expected Improvement (EI) method, proposed by Jones, Schonlau, andWelch, is a widely used Bayesian optimization method, which makes use of a fitted Gaussian process model for efficient black-box optimization. However, one key drawback of EI is that it is overly greedy in exploiting the fitted Gaussian process model for optimization, which results in suboptimal solutions even with large sample sizes. To address this, we propose a new hierarchical EI (HEI) framework, which…

cmenet：条件主效应的双层变量选择方法AI 解读

Simon Maka & C. F. Jeff Wua*a School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GACONTACT C. F. Jeff Wu jeffwu@isye.gatech.edu School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332.Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/r/JASA.Supplementary materials for this article are available online. Please go to…

支撑点：概率分布的代表点构造AI 解读

This paper introduces a new way to compact a continuous probability distribution $F$ into a set of representative points called support points. These points are obtained by minimizing the energy distance, a statistical potential measure initially proposed by Székely and Rizzo [InterStat 5 (2004) 1–6] for testing goodness-of-fit. The energy distance has two appealing features. First, its distance-based structure allows us to exploit the duality between powers of the Euclidean…

大涡模拟的高效代理模型与物理机制提取AI 解读

In the quest for advanced propulsion and power-generation systems, high-fidelity simulations are too computationally expensive to survey the desired design space, and a new design methodology is needed that combines engineering physics, computer simulations, and statistical modeling. In this article, we propose a new surrogate model that provides efficient prediction and uncertainty quantification of turbulent flows in swirl injectors with varying geometries, devices…