论文标题
单体反向差分类别
Monoidal Reverse Differential Categories
论文作者
论文摘要
笛卡尔反向差异类别（CRDC）是最近定义的结构，对监督学习中使用的反向分化操作进行了明显的建模。在这里，我们定义了一种称为单型反向差异类别的相关结构，证明了其与CRDC的关系的重要结果，并提供了这两种结构的示例，包括来自量子计算模型的示例。
Cartesian reverse differential categories (CRDCs) are a recently defined structure which categorically model the reverse differentiation operations used in supervised learning. Here we define a related structure called a monoidal reverse differential category, prove important results about its relationship to CRDCs, and provide examples of both structures, including examples coming from models of quantum computation.
