论文标题
在局部熵，随机控制和深神经网络上
On local entropy, stochastic control and deep neural networks
论文作者
论文摘要
在本文中，我们将一些有关能量景观平滑和基于评分的机器学习模型平滑的论文连接到随机控制中的经典工作。我们澄清了这些连接，提供了严格的陈述和表示形式，这些陈述和表示可以用作进一步学习模型的指南。
In this paper, we connect some recent papers on smoothing of energy landscapes and scored-based generative models of machine learning to classical work in stochastic control. We clarify these connections providing rigorous statements and representations which may serve as guidelines for further learning models.
