Large Graph Limits of Stochastic Processes on Random Graphs

随机图上随机过程的大图极限

• 批准号: EP/Y027795/1
• 负责人: Wasiur Rahman Khuda Bukhsh
• 金额: $ 10.19万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY027795%2F1
• 关键词: Large; Graph; Limits; Stochastic; Processes; Large; Graph; Limits; Stochastic; Processes

For a class of interacting particle systems on random graphs, we will develop new tools for parameter inference and prediction based on rigorous large-graph approximations and the Dynamic Survival Analysis (DSA) approach, which, compared to traditional methods, works with much smaller amounts of (possibly censored/truncated and/or aggregated) data.

对于随机图上的一类相互作用的粒子系统，我们将基于严格的大图近似值和动态生存分析（DSA）方法开发用于参数推理和预测的新工具，与传统方法相比，该方法可以使用较小数量的（可能审查/删除和/或聚集）数据。