论文标题
从四个向量的深度学习
Deep Learning From Four Vectors
论文作者
论文摘要
深网能够提高粒子物理实验中收集数据的统计能力的能力的早期示例是证明了在粒子动量列表上运行的这种网络（四个矢量）可以使用具有域知识工程设计的功能来胜过浅网络。描述了一个基准案例，并扩展了参数化网络。介绍了数据处理和体系结构的讨论，以及如何将物理知识纳入网络体系结构的描述。
An early example of the ability of deep networks to improve the statistical power of data collected in particle physics experiments was the demonstration that such networks operating on lists of particle momenta (four-vectors) could outperform shallow networks using features engineered with domain knowledge. A benchmark case is described, with extensions to parameterized networks. A discussion of data handling and architecture is presented, as well as a description of how to incorporate physics knowledge into the network architecture.
