Stochastic processes and applications DSBA 2026/2027: различия между версиями
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'''Assistants:''' | '''Assistants:''' | ||
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'''<span style="color:#0000FF">Final grade = round(0.25 × Quizzes + 0.35 × Midterm + 0.40 × Exam, 2)</span>''' | '''<span style="color:#0000FF">Final grade = round(0.25 × Quizzes + 0.35 × Midterm + 0.40 × Exam, 2)</span>''' | ||
Home assignments are almost surely released weekly. You do not need to submit regular home assignments: the following class includes a quiz with one or two problems some how based on the home assignment. At the end of the course you have 3 honey pots: a right to rewrite 3 missed or badly written quizzes. | Home assignments are almost surely released weekly. You do not need to submit regular home assignments: the following class includes a quiz with one or two problems some how based on the home assignment. At the end of the course you have 3 honey pots: a right to rewrite '''<span style="color:#A81C07">3</span>''' missed or badly written quizzes. | ||
== Sources of Wisdom == | == Sources of Wisdom == | ||
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=== Course materials === | === Course materials === | ||
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Текущая версия от 20:17, 18 сентября 2026
Course goals
侍には目標がなく道しかない [Samurai niwa mokuhyō ga naku michi shikanai]
A samurai has no goal, only a path.
Telegram chat
Teachers and assistants
Teachers: Пётр Лукьянченко Мария Кириллова Алёна Числова
Assistants:
| Name | Responsibilities / groups |
|---|---|
| Иван Новосад | Lecturer's assistant |
| Ева Каримова | Groups 243, 245 |
| Аскар Биктибаев | Group 244 |
| Ольга Макогонова | Groups 241, 242 |
Grading
Final grade = round(0.25 × Quizzes + 0.35 × Midterm + 0.40 × Exam, 2)
Home assignments are almost surely released weekly. You do not need to submit regular home assignments: the following class includes a quiz with one or two problems some how based on the home assignment. At the end of the course you have 3 honey pots: a right to rewrite 3 missed or badly written quizzes.
Sources of Wisdom
Enlightenment is not guaranteed. The reading list is a good start.
The resources below come from earlier course pages. Assignment files and recordings retain their original academic-year labels.
Course materials
| Resource | Links |
|---|---|
| Home assignments | SP 2025/26 · SP–TSA 2024/25 · 2023/24 |
| Lecture and class notes | 2025/26 notes · 2024/25 lecture slides and notes · Maria Kirillova's notes — 2024/25 |
| Videos — made with love | 2025/26 recordings · 2024/25 class recordings · Practice playlist |
| Past exams | Past exam collection · Сливы осеннего экзамена 2026 |
| Course whitepaper | Whitepaper linked on the 2024/25 and 2025/26 course pages |
Probability and Markov chains
- StoPro — Problems in Stochastic Processes
- Introduction to Probability — Blitzstein and Hwang
- Cambridge lectures on Markov chains
- Takis Konstantopoulos — One Hundred Solved Exercises on Markov Chains
- Representing Markov Chains in LaTeX
- Convergence modes — Cornell review
- Convergence modes with examples — Saravanan Vijayakumaran
- Statistics Cookbook
Monte Carlo and MCMC
- Chib and Greenberg — Understanding the Metropolis–Hastings Algorithm
- Casella — Explaining the Gibbs Sampler
- Roberts and Rosenthal — General State Space Markov Chains
- Visualization of MCMC methods
- Charles Geyer — MCMC lecture notes
Stochastic calculus
- Zastawniak — Basic Stochastic Processes.
- ICEF master's course exams
- ICEF master's course notes — Russian
- Draft textbook — Russian
- Draft problem collection — Russian
Previous paths
The path continues, almost surely.