Математические методы прогнозирования (практика, В.В. Стрижов)/Группа 574, осень 2019
Материал из MachineLearning.
Short link bit.ly/IS_B2
Группа
5 курс
| Студент | Тест 1 | Тест 2 | Тест 3 | HW 1 | HW 2 |
|---|---|---|---|---|---|
| Васильев Илья | - | - | 0.59 | - | |
| Гадаев Тамаз Тазикоевич | 0.56 | 0.94 | 0.75 | - | |
| Гладин Егор Леонидович | - | - | - | - | |
| Грабовой Андрей Валериевич | 0.63 | 0.31 | 0.67 | Essay | |
| Кислинский Вадим Геннадьевич | - | - | - | - | |
| Козлинский Евгений Михайлович | - | - | - | - | |
| Криницкий Константин Денисович | - | 0.25 | - | essay | |
| Кириллов Егор Дмитриевич | - | - | - | - | |
| Рогозина Анна Андреевна | - | - | - | - | |
| Плетнев Никита Вячеславович | 0.82 | 0.25 | 0.67 | Essay | |
| Малиновский Григорий Станиславович | 0.82 | 0.81 | 0.84 | [1] | |
| Самохина Алина Максимовна | - | - | 0.25 | - | |
| Султанов Азат Русланович | - | - | - | - | |
| Федосов Павел Андреевич | - | - | - | - | |
| Шульгин Егор Владимирович | - | - | 0.34 | - |
6 курс
| Студент | HW 1 | HW 2 |
|---|---|---|
| Сайранов Данил | - | |
| Фельдман Даниил | - | |
| Никитин Филипп | - | |
| Фалахов И | - | |
| Собраков | - |
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, slides)
- Mean field approximation
- Flow models (NICE, RealNVP)
Seminar 4 (Isachenko, slides)
- VAE Limitations
- Flows in VAE
- Autoregressive flows (MAF, IAF, Parallel WaveNet)
- 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
