Monte Carlo

Bayesian Inference for Partially Observed Continuous-Time Processes

Amin Wu, Ph.D. Student, Statistics

Mar 3, 10:00 - 12:00

B5 L5 R5220

McKean-Vlasov SDEs bayesian inference markov chains Monte Carlo

This thesis develops Bayesian inference methods for partially observed stochastic differential equations (SDEs) with unknown parameters, focusing on the stochastic Volterra equation (SVE), non-synchronous diffusions, and McKean-Vlasov SDEs. Employing Euler-Maruyama discretization.