Stochastic Differential Equations: Mean-Field Inference

This lecture covers the inference for multiscale and mean-field stochastic differential equations, focusing on numerical methods and convergence analysis. It discusses joint papers with Assyr Abdulle, including topics like accelerated convergence, drift estimation, and eigenfunction martingale estimating functions. The presentation also delves into the methodology of drift estimation based on filtered data and the sensitivity analysis of estimators. The lecture concludes with a discussion on the joint diffusive-mean field limit and the commutativity of mean field and homogenization limits.