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== About the course ==
 
== About the course ==
 
This page contains materials for Markov Chains course in 2023/2024 year, mandatory one for 1st year Master students of the MML program (HSE and Skoltech).
 
This page contains materials for Markov Chains course in 2023/2024 year, mandatory one for 1st year Master students of the MML program (HSE and Skoltech).
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Link to telegram chat: https://t.me/+9bDEStkmdi0xMWVi
  
 
== Grading ==  
 
== Grading ==  
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== Lectures ==
 
== Lectures ==
* [https://disk.yandex.ru/i/LsKhx0pCNo5rag Lecture №1, 09.11]
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* [https://disk.yandex.ru/i/UN0f7EuYK0G9jQ Lecture №1, 09.11]
* [https://disk.yandex.ru/i/gm4ch7k5ollvFw Lecture №2, 18.11]
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* [... Lecture №2, 18.11]
* ... Lecture №3, 25.11]
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* [https://disk.yandex.ru/i/c3wEPZ1zYaCI_g Lecture №3, 25.11]
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* [https://disk.yandex.ru/i/CfhWKmbAOaEgEw Lecture №4, 02.12]
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* [https://disk.yandex.ru/d/nM_XKLm4BfILhw Lecture №5-6, 16.12]
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* [https://disk.yandex.ru/i/I8M-SoWlLHl3Ag Lecture №7, 13.01]
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* [https://disk.yandex.ru/i/7F6gH0mFBcnn_w Lecture №8, 20.01]
  
 
== Seminars ==
 
== Seminars ==
TBD
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https://disk.yandex.ru/d/cXeyH_vL3fEb_g
  
 
== Homeworks ==
 
== Homeworks ==
TBD
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To submit homework, join
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[https://classroom.google.com/c/NjM4ODgyNjE1ODEw?cjc=y6dk72i '''Google classroom'''] — invite code '''y6dk72i'''
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Homework solution file should be readable and well-organized.
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* [https://disk.yandex.ru/i/UH2fNs3vp6qtFA Homework 1: Deadline 13.01.2024, 23:59]
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* [https://disk.yandex.ru/i/S2MdBKkH4_J0jA Homework 2: Deadline 03.02.2024, 23:59]
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* [https://disk.yandex.ru/i/WVysij7PyiKD4Q Homework 3: Deadline 17.03.2024, 23:59]
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* [https://disk.yandex.ru/i/xFgnBzy6GNy2Uw Homework 4: Deadline 23.03.2024, 23:59]
  
 
== Exam ==
 
== Exam ==
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*https://link.springer.com/book/10.1007%2F978-3-319-62226-2 - Stochastic Calculus by P. Baldi, good overview of conditional probabilities and expectations (part 4, also accessible through HSE network)
 
*https://link.springer.com/book/10.1007%2F978-3-319-62226-2 - Stochastic Calculus by P. Baldi, good overview of conditional probabilities and expectations (part 4, also accessible through HSE network)
 
*https://elearning.unimib.it/pluginfile.php/583708/mod_resource/content/1/1-conditional-law.pdf - Probability kernels and (regular) conditional probabilities, to the third lecture.
 
*https://elearning.unimib.it/pluginfile.php/583708/mod_resource/content/1/1-conditional-law.pdf - Probability kernels and (regular) conditional probabilities, to the third lecture.
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== Useful links ==
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Energy based models:
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*Tutorial from seminar: https://uvadlc-notebooks.readthedocs.io/en/latest/tutorial_notebooks/tutorial8/Deep_Energy_Models.html
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*Important work on EBM: https://openai.com/research/energy-based-models
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*Other EBM related works of the same author: https://energy-based-model.github.io/Energy-based-Model-MIT/
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*Another tutorial on EBM from CVPR 2021: https://energy-based-models.github.io/
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*Another tutorial on EBM from Yann LeCun: https://www.cs.toronto.edu/~vnair/ciar/lecun1.pdf
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*Comparisson between generative models: https://arxiv.org/pdf/2103.04922.pdf

Текущая версия на 12:38, 9 марта 2024

Lecturers and Seminarists

Lecturer Samsonov Sergey [svsamsonov@hse.ru] T902
Seminarist Artur Goldman [...] T926

About the course

This page contains materials for Markov Chains course in 2023/2024 year, mandatory one for 1st year Master students of the MML program (HSE and Skoltech).

Link to telegram chat: https://t.me/+9bDEStkmdi0xMWVi

Grading

The final grade consists of 3 components (each is non-negative real number from 0 to 10, without any intermediate rounding) :

  • OHW for the hometasks
  • OMid-term for the midterm exam
  • OExam for the final exam

The formula for the final grade is

  • OFinal = 0.35*OHW + 0.3*OMid-term + 0.35*OExam

with the usual (arithmetical) rounding rule.

[... Table with grades]

Lectures

Seminars

https://disk.yandex.ru/d/cXeyH_vL3fEb_g

Homeworks

To submit homework, join Google classroom — invite code y6dk72i

Homework solution file should be readable and well-organized.

Exam

TBD

Midterm

TBD

Recommended literature (1st term)

Useful links

Energy based models: