图形PPL.jl:用于图形模型的概率编程语言
Wouter W L Nuijten1, Dmitry Bagaev1, Bert de Vries1,2
1Department of Electrical Engineering, Eindhoven University of Technology, 5612 AE Eindhoven, The Netherlands.
GraphPPL.jl是一种用于图形模型的新型概率编程语言,使用因子图和模型嵌套来简化开发. 它支持模块化,并通过插件系统与推理引擎集成.
科学领域:
- 人工智能的人工智能
- 机器学习 机器学习
- 可能性的图形模型
背景情况:
- 开发复杂的概率图形模型可能具有挑战性.
- 整合各种推断引擎与模型定义往往需要大量的努力.
研究的目的:
- 介绍 GraphPPL.jl,这是一个用于图形模型的新型概率编程语言.
- 简化模块化和层次化的图形模型的创建和管理.
- 为整合各种推理引擎提供灵活的框架.
主要方法:
- 将概率模型表示为因子图.
- 实现模型嵌套以实现模块化.
- 开发一个用于推断引擎集成的插件系统.
- 使用受约束之间的自由能量最小化来证明变异推理.
主要成果:
- GraphPPL.jl允许模块化和层次化的图形模型开发.
- 插件系统促进了与多个推理后端的无集成.
- 作为一个变量推理方法,被限制的Bethe自由能量最小化得到了支持.
- 该语言在模型定义和推理之间提供了明确的分离.
结论:
- GraphPPL.jl是一个强大的,富有表达力和用户友好的图形模型语言.
- 它简化了复杂的模型开发和推理.
- 为开发人员提供可扩展性和定制性,作为高级界面.
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