论文标题
估计样品特征的平均值：卷积神经网络方法
Estimation of the Sample Frechet Mean: A Convolutional Neural Network Approach
论文作者
论文摘要
这项工作通过提出快速算法来计算样本Frechet均值来解决“图值随机变量”中对“图值随机变量”中对新工具的需求的不断增加，这取代了图形（或网络）的样本平均值概念。我们使用卷积神经网络在一组图中学习图形的形态。我们对几个随机图集合的实验表明，我们的方法可以可靠地恢复样品平均值。
This work addresses the rising demand for novel tools in statistical and machine learning for "graph-valued random variables" by proposing a fast algorithm to compute the sample Frechet mean, which replaces the concept of sample mean for graphs (or networks). We use convolutional neural networks to learn the morphology of the graphs in a set of graphs. Our experiments on several ensembles of random graphs demonstrate that our method can reliably recover the sample Frechet mean.
