Математические методы прогнозирования (практика, В.В. Стрижов)/Группа 574, осень 2019
Материал из MachineLearning.
(Различия между версиями)
(→Группа) |
|||
Строка 13: | Строка 13: | ||
! Тест 2 | ! Тест 2 | ||
! Тест 3 | ! Тест 3 | ||
+ | ! Тест 4 | ||
! HW 1 | ! HW 1 | ||
! HW 2 | ! HW 2 | ||
Строка 20: | Строка 21: | ||
| - | | - | ||
| 0.59 | | 0.59 | ||
+ | | - | ||
| - | | - | ||
| | | | ||
Строка 27: | Строка 29: | ||
| 0.94 | | 0.94 | ||
| 0.75 | | 0.75 | ||
+ | | - | ||
| - | | - | ||
| | | | ||
Строка 34: | Строка 37: | ||
| - | | - | ||
| - | | - | ||
+ | | - | ||
| - | | - | ||
| | | | ||
Строка 41: | Строка 45: | ||
| 0.31 | | 0.31 | ||
| 0.67 | | 0.67 | ||
+ | | 0 | ||
|[[Media:Grabovoy2019Course5HM1.pdf|Essay]] | |[[Media:Grabovoy2019Course5HM1.pdf|Essay]] | ||
| | | | ||
|- | |- | ||
| Кислинский Вадим Геннадьевич | | Кислинский Вадим Геннадьевич | ||
+ | | - | ||
| - | | - | ||
| - | | - | ||
Строка 52: | Строка 58: | ||
|- | |- | ||
| Козлинский Евгений Михайлович | | Козлинский Евгений Михайлович | ||
+ | | - | ||
| - | | - | ||
| - | | - | ||
Строка 61: | Строка 68: | ||
| - | | - | ||
| 0.25 | | 0.25 | ||
+ | | - | ||
| - | | - | ||
|[https://drive.google.com/file/d/1xk2uvz6FmWz0s1SCleF56pRFsTlXvQ8_/view?usp=sharing essay] | |[https://drive.google.com/file/d/1xk2uvz6FmWz0s1SCleF56pRFsTlXvQ8_/view?usp=sharing essay] | ||
Строка 66: | Строка 74: | ||
|- | |- | ||
| Кириллов Егор Дмитриевич | | Кириллов Егор Дмитриевич | ||
+ | | - | ||
| - | | - | ||
| - | | - | ||
Строка 73: | Строка 82: | ||
|- | |- | ||
| Рогозина Анна Андреевна | | Рогозина Анна Андреевна | ||
+ | | - | ||
| - | | - | ||
| - | | - | ||
Строка 83: | Строка 93: | ||
| 0.25 | | 0.25 | ||
| 0.67 | | 0.67 | ||
+ | | - | ||
|[https://drive.google.com/a/phystech.edu/file/d/1kkqHZDR2ATzWtf8FRc8BjbcNAXaApvy1/view?usp=drivesdk Essay] | |[https://drive.google.com/a/phystech.edu/file/d/1kkqHZDR2ATzWtf8FRc8BjbcNAXaApvy1/view?usp=drivesdk Essay] | ||
| | | | ||
Строка 90: | Строка 101: | ||
| 0.81 | | 0.81 | ||
| 0.84 | | 0.84 | ||
+ | | 1 | ||
||[https://drive.google.com/file/d/1UkmIDJgZEDTtzSk_a20IZlTy62F2tnJB/view?usp=sharing|task_1] | ||[https://drive.google.com/file/d/1UkmIDJgZEDTtzSk_a20IZlTy62F2tnJB/view?usp=sharing|task_1] | ||
| | | | ||
Строка 97: | Строка 109: | ||
| - | | - | ||
| 0.25 | | 0.25 | ||
+ | | 1 | ||
| - | | - | ||
| | | | ||
|- | |- | ||
| Султанов Азат Русланович | | Султанов Азат Русланович | ||
+ | | - | ||
| - | | - | ||
| - | | - | ||
Строка 108: | Строка 122: | ||
|- | |- | ||
| Федосов Павел Андреевич | | Федосов Павел Андреевич | ||
+ | | - | ||
| - | | - | ||
| - | | - | ||
Строка 118: | Строка 133: | ||
| - | | - | ||
| 0.34 | | 0.34 | ||
+ | | - | ||
| - | | - | ||
| | | |
Версия 16:07, 2 октября 2019
Short link bit.ly/IS_B2
Группа
5 курс
Студент | Тест 1 | Тест 2 | Тест 3 | Тест 4 | 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 | 0 | 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 | [1] | |
Самохина Алина Максимовна | - | - | 0.25 | 1 | - | |
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 5 (Isachenko, slides)
- IWAE (lower bound, posterior, inactive units)
- ELBO surgery
- VampPrior
- 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