Numerical Methods and Stochastics
This work aims to identify emerging ideas in probability theory that influence future work in both probability and numerical computation. It focuses on novel approaches to computational problems based on cutting-edge techniques from the theory of probability and stochastic processes.
This volume represents the proceedings of the Workshop on Numerical Methods and Stochastics held at The Fields Institute in April 1999. The goal of the workshop was to identify emerging ideas in probability theory that influence future work in both probab
D. Crisan: Numerical methods for solving the stochastic filtering problem. D. Crisan and T. Lyons: Optimal filtering on discrete sets. P. Del Moral and J. Jacod: The Monte-Carlo method for filtering with discrete-time observations: Central limit theorems. A. Guionnet: Approximations of Markovian non linear partial differential equations by particle systems. A. Guionnet: Non-Markovian limit diffusions and spin glasses. S. B. Hazra and F. G. Viens: Towards pathwise stochastic fast dynamo in magneto-hydrodynamics. T. J. Lyons: System control and rough paths. J. B. Walsh and O. D. Walsh: Embedding and the convergence of the binomial and trinomial tree schemes