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Found 4 papers, 1 papers with code
基于有向异构图的发票明细税收分类方法(Tax Classification of Invoice Details Based on Directed Heterogeneous Graph)
税收是国家赖以生存的物质基础。为加快税收现代化, 方便纳税人便捷、规范开具增值税发票, 国税总局规定纳税人在税控系统开票前选择发票明细对应的税收分类才可正常开具发票。提高税收分类的准确度, 是构建税收风险指标和分析纳税人行为特征的重要基础。基于此, 本文提出了一种基于有向异构图的短文本分类模型(Heterogeneous Directed Graph Attenton Network, HDGAT), 利用发票明细间的有向信息建模, 引入外部知识, 显著地提高了发票明细的税收分类准确度。
Dynamic Security Region of Natural Gas Systems in Integrated Electricity-Gas Systems
In an integrated electricity-gas system (IEGS), the tight coupling of power and natural gas systems is embodied by frequent changes in gas withdrawal from gas-fired units to provide regulation services for the power system to handle uncertainty, which may in turn endanger the secure operation of the natural gas system and ultimately affect the safety of the whole IEGS.
Coarse-to-Fine Contrastive Learning on Graphs
Inspired by the impressive success of contrastive learning (CL), a variety of graph augmentation strategies have been employed to learn node representations in a self-supervised manner.
TEAC: Intergrating Trust Region and Max Entropy Actor Critic for Continuous Control
Trust region methods and maximum entropy methods are two state-of-the-art branches used in reinforcement learning (RL) for the benefits of stability and exploration in continuous environments, respectively.
