论文标题
ganplifying事件样本
GANplifying Event Samples
论文作者
论文摘要
关于粒子物理中事件产生的生成网络的一个关键问题是，生成事件是否增加了训练样本以外的统计精度。我们显示了一个简单的示例，即生成网络确实如何扩大培训统计数据，并增加了维度。我们通过放大因子或同等数量的采样事件来量化它们的影响。
A critical question concerning generative networks applied to event generation in particle physics is if the generated events add statistical precision beyond the training sample. We show for a simple example with increasing dimensionality how generative networks indeed amplify the training statistics. We quantify their impact through an amplification factor or equivalent numbers of sampled events.
