Spring 2023 Applied Mathematics E4306 section 001

Applied Stochastic Analysis

Applied Stochastic Analys

Call Number 13137
Day & Time
Location
MW 10:10am-11:25am
524 Seeley W. Mudd Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Shanyin Tong
Type LECTURE
Method of Instruction In-Person
Course Description

Non Course Prerequisites: Elementary probability theory (IEOR E3658 or above) and stochastic process (on the level of the first part of IEOR E4106 or STAT G4264) are required. Knowledge on analysis (MATH GU4601 or above) and differential equations (APMA E4200 or above) are required. Knowledge on numerical methods (APMA E4300 and above) and programming skills are required.

Provides elementary introduction to fundamental ideas in stochastic analysis for applied mathematics. Core material includes: (i) review of probability theory (including limit theorems), and introduction to discrete Markov chains and Monte Carlo methods; (ii) elementary theory of stochastic process, Ito's stochastic calculus and stochastic differential equations; (iii) introductions to probabilistic representation of elliptic partial differential equations (the Fokker-Planck equation theory); (iv) stochastic approximation algorithms; and (v) asymptotic analysis of SDEs.

Web Site Vergil
Department Applied Physics and Applied Mathematics
Enrollment 14 students (50 max) as of 10:06AM Sunday, February 25, 2024
Subject Applied Mathematics
Number E4306
Section 001
Division School of Engineering and Applied Science: Graduate
Open To Columbia College, Engineering:Undergraduate, Engineering:Graduate, GSAS, General Studies
Campus Morningside
Note EARLY REGISTRATION FOR APAM ONLY, OTHER DEPTS JAN 10TH
Section key 20231APMA4306E001