Maria K. Cameron

University of Maryland, Department of Mathematics

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MATH858D: Stochastic Methods with Applications

The goal of this course is to give an introduction to stochastic methods for the analysis and the study of complex physical, chemical, and biological systems, and their mathematical foundations.

Syllabus, Spring 2021

Basic concepts of Probability

Lecture notes: prob_basic_concepts.pdf
Homework: HW1


Lecture notes: sampling.pdf
Homework: HW2

Markov Chains

Lecture notes: markov_chains.pdf
Homework: HW3, HW4, HW5, HW6,

Brownian Motion

Lecture notes: SDEs.pdf
Homework: HW7, HW8

An Introduction into the Large Deviation Theory

Lecture notes: LDT.pdf
Homework: HW9, HW10, LJ6in2Dsetup.m

An Introduction to data analysis

Lecture notes: DiffusionMapsMATH858T.pdf
Take-home final 2021: final2021.pdf, gmam.m

Some additional course materials from Spring 2019

An introduction to data analysis
Codes: -- codes mimic those from [1]
Lecture notes: data_analysis.pdf
Homework: HW7, SubjSim12countries.mat, MakeSprial.m

Codes: Paths﹠ - MATLAB codes for finging transition paths and trasition states
Take-home final 2019