Математические методы прогнозирования (практика, В.В. Стрижов)/Группа 574, осень 2019

Материал из MachineLearning.

(Различия между версиями)
Перейти к: навигация, поиск
Строка 3: Строка 3:
Short link [http://bit.ly/IS_B2 bit.ly/IS_B2]
Short link [http://bit.ly/IS_B2 bit.ly/IS_B2]
 +
 +
=== Группа ===
 +
{|class="wikitable"
 +
|-
 +
! Студент
 +
! Баллы
 +
|-
 +
|[[Участник:andriygav|Грабовой Андрей]]
 +
|
 +
|-
 +
|}
 +
This series of seminars continues the course Bayesian model selection and investigates the theoretical aspects of model selection in various application problems.
This series of seminars continues the course Bayesian model selection and investigates the theoretical aspects of model selection in various application problems.

Версия 17:03, 16 сентября 2019


Short link bit.ly/IS_B2

Группа

Студент Баллы
Грабовой Андрей


This series of seminars continues the course Bayesian model selection and investigates the theoretical aspects of model selection in various application problems.

Seminar 1 (Isachenko, slides)

  • Generative models
  • Applications
  • Autoregressive models (CharRNN, MADE, WaveNet, PixelCNN)

Seminar 2 (Isachenko, slides)

  • Generative vs discriminative
  • Latent variable models
  • Variational Inference
  • ELBO
  • Variational Autoencoder






  • Seminar 3 (Isachenko)
    • Inference methods of approximation
    • Zoo of variational autoencoders and practical examples
  • Seminar 4 (Isachenko)
    • Generative adversarial networks
  • Seminar 5 (Bakhteev)
    • Methods of model selection
    • Generalization theorem
  • Seminar 6 (Bakhteev)
    • Complexity theorems
  • Seminar 7 (Grabovoy?)
    • Mixture of experts
    • Priors on the mixture
    • Privileged learning and distilling
  • Seminar 8 (Aduenko?)
    • Theorem of number of experts
  • Seminar 9 (Vladimirova?)
    • Prior propagation for deep learning networks
  • Seminar 10
    • Directional Bayesian statistics
  • Seminar 11
    • Bayesian structure learning
  • Seminar 12
    • Probabilistic metric space construction
  • Seminar 13
    • Informative prior
  • Seminar 14
    • Bayesian programming






  • Informative prior with applications
Личные инструменты