Overview
MATH5805 is an honours and postgraduate course. See the聽聽below.聽 聽
Special Topics in Statistics title: "A Modern Introduction to Extreme Value Theory"聽 聽- please refer to this Flyer for Term 1 2025 offering here
Units of credit:听6
Prerequisites: Nil
Cycle of offering:聽Not offered every year
Graduate attributes:聽The course will enhance your research, inquiry and analytical thinking abilities.
More information:聽聽The Course outline will be made available closer to the start of term - please visit this website:聽聽www.unsw.edu.au/course-outlines
The course handout contains information about course objectives, assessment, course materials and the syllabus.聽
Important additional information as of 2023
UNSW Plagiarism Policy
The University requires all students to be aware of its聽.
For courses convened by the聽School of Mathematics and Statistics no assistance using generative AI software is allowed unless specifically referred to in the individual assessment tasks.
If its use is detected in the no assistance case, it will be regarded as serious academic misconduct and subject to the standard penalties, which may include 00FL, suspension and exclusion.
罢丑别听聽contains聽information about the course. The timetable is only up-to-date if the course is being offered this year.
If you are currently enrolled in MATH5805, you can log into聽聽for this course.
Course overview
This course will cover topics in the general area of Monte Carlo methods and their application domains. The topics include Markov chain Monte Carlo and Sequential Monte Carlo methods,Quantum and Diffusion Monte Carlo techniques, as well as branching and interacting particle methodologies. The lectures cover discrete and continuous time stochastic models, starting from traditional sampling techniques (perfect simulation, Metropolis-Hasting, and Gibbs-Glauber models) to more refined methodologies such as gradient flows diffusions on constraint state space and Riemannian manifolds, ending with the more recent and rapidly developing Branching and mean field type Interacting Particle Systems techniques.