论文标题
广告/深度学习变得简单：简单的例子
AdS/Deep-Learning made easy: simple examples
论文作者
论文摘要
深度学习已在各个研究领域被广泛而积极地使用。最近，在量规/重力二重性中，已经提出了一种新的深度学习技术，所谓的广告/深学习（DL）[1，2]。本文的目的是在最简单的设置中描述ADS/DL的本质，对于那些希望将其应用于新兴时空作为神经网络的人。对于原型示例，我们选择简单的经典力学问题。从某种意义上说，这种方法与标准深度学习技术有些不同，因为我们不仅有正确的最终答案，而且还获得了对学习参数的物理理解。
Deep learning has been widely and actively used in various research areas. Recently, in the gauge/gravity duality, a new deep learning technique so-called the AdS/Deep-Learning (DL) has been proposed [1, 2]. The goal of this paper is to describe the essence of the AdS/DL in the simplest possible setups, for those who want to apply it to the subject of emergent spacetime as a neural network. For prototypical examples, we choose simple classical mechanics problems. This method is a little different from standard deep learning techniques in the sense that not only do we have the right final answers but also obtain a physical understanding of learning parameters.
