Scalable Monte Carlo Methods for large-scale infererence

我们正处于大数据和大模型的时代。在这种情况下，标准蒙特卡罗方法，如马尔可夫链蒙特卡罗方法不缩放，即计算复杂度太高。本项目的目标是开发、分析和应用新的可扩展蒙特卡罗方法，特别适合在大规模分布式系统上实现。该项目将属于EPSRC统计和应用概率研究领域

We are in the era of Big Data and big models. In this context, standard Monte Carlo methods such as Markov Chain Monte Carlo methods do not scale, ie the computational complexity is far too high. The aim of the DPhil is to develop, analyse and apply new scalable Monte Carlo methods, which are particularly suitable for an implementation on large-scale distributed systems.The project will fall within the EPSRC statistics and applied probability research area