深度学习技术在对撞机硬散射过程分析中的应用

Proceedings of The 5th International Workshop on Deep Learning in Computational Physics — PoS(DLCP2021) Pub Date : 2021-09-14 DOI:10.22323/1.410.0012

L. Dudko, P. Volkov, G. Vorotnikov, A. Zaborenko

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引用次数: 0

摘要

深度神经网络理所当然地赢得了高能物理中最精确的分析工具之一的地位。在本文中，我们将介绍几种方法，以顶夸克分析为例，提高深度神经网络在分类任务中的性能。方法和建议将涵盖超参数调优，提高错误和应用于对撞机物理的AutoML算法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Application of Deep Learning Technique to an Analysis of Hard Scattering Processes at Colliders

Deep neural networks have rightfully won the place of one of the most accurate analysis tools in high energy physics. In this paper we will cover several methods of improving the performance of a deep neural network in a classification task in an instance of top quark analysis. The approaches and recommendations will cover hyperparameter tuning, boosting on errors and AutoML algorithms applied to collider physics.

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Proceedings of The 5th International Workshop on Deep Learning in Computational Physics — PoS(DLCP2021)

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