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Sixth Machine Learning in High Energy Physics Summer School 2020

from Thursday 16 July 2020 (09:00) to Thursday 30 July 2020 (20:30)
Zoom

        : Sessions
    /     : Talks
        : Breaks
16 Jul 2020
17 Jul 2020
18 Jul 2020
19 Jul 2020
20 Jul 2020
21 Jul 2020
22 Jul 2020
23 Jul 2020
24 Jul 2020
25 Jul 2020
27 Jul 2020
28 Jul 2020
29 Jul 2020
30 Jul 2020
AM
09:00 Welcome, opening words - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))  
09:30 Practice. Getting familiar with school infrastructure - Vladislav Belavin (Yandex School of Data Analysis (RU)) Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))  
10:00 --- Break ---
10:15 Intro into Machine Intelligence - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))  
11:30
Section 1. Introduction into ML - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 12:45)
11:30 Introduction into supervised learning - Artem Maevskiy (National Research University Higher School of Economics (RU))  
12:00 Seminar: Data Handling in Python - Artem Maevskiy (National Research University Higher School of Economics (RU))  
09:00
Section 1. Introduction into ML - Mikhail Hushchyn (Yandex School of Data Analysis (RU)) (until 10:00)
09:00 Quality Metrics-1 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))  
09:30 Seminar: Quality Metrics-1  
10:00 --- Break ---
10:30
Section 1. Introduction into ML - Mikhail Hushchyn (Yandex School of Data Analysis (RU)) (until 11:30)
10:30 Quality Metrics-2 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))  
11:00 Seminar: Quality Metrics-2 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))  
11:30 --- Break ---
09:00
Section 1. Introduction into ML - Mikhail Hushchyn (Yandex School of Data Analysis (RU)) (until 10:00)
09:00 Useful hacks - Mikhail Hushchyn (Yandex School of Data Analysis (RU))  
09:30 Seminar: Useful hacks. - Mikhail Hushchyn (Yandex School of Data Analysis (RU))  
10:00 --- Break ---
10:30
Section 1. Introduction into ML - Mikhail Hushchyn (Yandex School of Data Analysis (RU)) (until 11:30)
10:30 Clustering-1 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))  
11:00 Seminar: Clustering-1 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))  
11:30 --- Break ---
09:00 --- Sunday ---
09:00
Section 2. Introduction into Neural Networks - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 10:00)
09:00 Intro to NN - Artem Maevskiy (National Research University Higher School of Economics (RU))  
09:20 Seminar: Intro to NN - Artem Maevskiy (National Research University Higher School of Economics (RU))  
10:00 --- Break ---
10:30
Section 2. Introduction into Neural Networks - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)) (until 11:30)
10:30 Intro to Pytorch - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))  
11:00 Seminar: Pytorch practice - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))  
11:30 --- Break ---
09:00
Section 2. Introduction to Neural Nets - Artem Ryzhikov (National Research University Higher School of Economics (RU)) (until 10:00)
09:00 Autoregressive networks-2  
09:30 Seminar: Autoregressive networks-2  
10:00 --- Break ---
10:30
Section 2. Introduction to Neural Nets - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 11:30)
10:30 Network architectures: tips and tricks  
11:10 Seminar: Practice  
11:30 --- Break ---
09:00
Section 3. Bayesian Deep Learning - Ekaterina Lobacheva (until 10:00)
09:00 Variational Inference  
09:30 Seminar: Variational Inference  
10:00 --- Break ---
10:30
Section 3. Bayesian Deep Learning - Nadya Chirkova (until 11:30)
11:30 --- Break ---
09:00
Section 3. Bayesian Deep Learning (until 10:00)
09:00 VAE  
09:30 Seminar: VAE  
10:00
Section 3. Bayesian Deep Learning - Alexei Struminsky (Space Research Institute) (until 10:30)
10:30 --- Break ---
11:00
Section 4. Generative models and networks - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 11:30)
11:30
Section 4. Generative models and networks - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 12:00)
09:00
Section 4. Generative models and networks - Artem Ryzhikov (National Research University Higher School of Economics (RU)) (until 10:00)
09:00 Autoencoders  
09:30 Seminar: Practice on AE  
10:00 --- Break ---
10:30
Section 4. Generative models and networks - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 11:30)
10:30 GANs  
11:00 Seminar: GANs  
11:30 --- Break ---
09:00
Section 5. Advanced Optimization Methods - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 10:00)
09:00 Introduction to black-box optimization  
09:30 Seminar: Introduction to black-box optimization  
10:00 --- Break ---
10:30
Section 5. Advanced Optimization Methods -Mr Vladislav Belavin (Yandex School of Data Analysis (RU)) (until 11:30)
11:30 --- Break ---
09:00
Section 5. Advanced Optimization Methods - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 10:00)
09:00 Bayesian Optimization  
09:30 Seminar: Bayesian Optimization  
10:00 --- Break ---
10:30
Section 5. Advanced Optimization Methods - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 11:30)
10:30 BO-GP and friends  
11:00 Seminar: BO-GP and friends  
11:30 --- Break ---
09:00
Section X - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 10:00)
09:00 Learning to pivot  
09:20 Seminar: Learning to pivot  
10:00 --- Break ---
10:30
Section X (until 12:30)
09:00
Section X - Denis Derkach (National Research University Higher School of Economics (RU)) (until 10:00)
10:00 --- Break ---
10:30
Section X - Denis Derkach (National Research University Higher School of Economics (RU)) (until 11:30)
11:30 --- Break ---
09:00
Guest lectures (until 10:30)
10:30 --- Break ---
11:30
Socialization (until 13:00)
PM
12:45 --- Lunch ---
13:30
Section 1. Introduction into ML - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 14:30)
13:30 Linear Regression - Artem Maevskiy (National Research University Higher School of Economics (RU))  
14:00 Seminar - Artem Maevskiy (National Research University Higher School of Economics (RU))  
14:30 --- Break ---
15:00
Section 1. Introduction into ML - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 16:00)
15:00 Logistic regression-1 - Artem Maevskiy (National Research University Higher School of Economics (RU))  
15:30 Seminar  
16:00 --- Break ---
16:30
Section 1. Introduction into ML - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 17:30)
16:30 Logistic regression-2 - Artem Maevskiy (National Research University Higher School of Economics (RU))  
17:00 Seminar - Artem Maevskiy (National Research University Higher School of Economics (RU))  
12:00
Section 1. Introduction into ML - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 13:00)
12:00 Decision trees-1 - Mr Nikita Kazeev (Yandex School of Data Analysis (RU))  
12:30 Seminar: Decision trees-1 - Nikita Kazeev (Yandex School of Data Analysis (RU))  
13:00 --- Lunch ---
14:00
Section 1. Introduction into ML - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 15:00)
14:00 Ensembles-1 - Nikita Kazeev (Yandex School of Data Analysis (RU))  
14:30 Seminar: Ensembles-1 - Nikita Kazeev (Yandex School of Data Analysis (RU))  
15:00 --- Break ---
15:30
Section 1. Introduction into ML - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 16:30)
15:30 Ensembles-2 - Nikita Kazeev (Yandex School of Data Analysis (RU))  
16:00 Seminar: Ensembles-2 - Nikita Kazeev (Yandex School of Data Analysis (RU))  
16:30 Coopetition introduction (1) - Mr Nikita Kazeev (Yandex School of Data Analysis (RU))  
17:00 --- Break ---
17:30
Socialization (until 18:30)
12:00
Section 1. Introduction into ML - Mikhail Hushchyn (Yandex School of Data Analysis (RU)) (until 13:00)
12:00 Clustering-2 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))  
12:30 Seminar: Clustering-2 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))  
12:00
Section 2. Introduction into Neural Networks - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)) (until 13:00)
12:00 CNN - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))  
12:30 Seminar: CNN - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))  
13:00 --- Lunch ---
14:00
Section 2. Introduction into Neural Networks - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 15:00)
14:00 Network regularization  
14:30 Seminar: Network regularization  
15:00 --- Break ---
15:30
Section 2. Introduction to Neural Nets - Artem Ryzhikov (National Research University Higher School of Economics (RU)) (until 16:30)
15:30 Autoregressive networks  
16:00 Seminar: Autoregressive networks  
16:30 --- Break ---
17:00
Guest lectures - Tommaso Dorigo (Universita e INFN, Padova (IT)) (until 18:30)
12:00
Section 3. Bayesian Deep Learning - Ekaterina Lobacheva (until 13:00)
12:00 Intro  
12:30 Seminar: Intro  
13:00 --- Lunch ---
14:00
Section 3. Bayesian Deep Learning - Ekaterina Lobacheva (until 15:00)
14:00 Full Bayesian Inference  
14:30 Seminar: Full Bayesian Inference  
15:00 --- Break ---
15:30
Section 3. Bayesian Deep Learning - Nadya Chirkova (until 16:00)
16:00 --- Break ---
16:30
Guest lectures (until 18:00)
12:00
Section 3. Bayesian Deep Learning - Nadya Chirkova (until 13:30)
12:00 Bayesian Neural Networks - Introduction  
12:30 Bayesian Neural Networks - Training  
13:30 --- Lunch ---
14:30
Section 3. Bayesian Deep Learning - Nadya Chirkova (until 15:30)
14:30 Seminar: Bayesian Neural Networks - Training  
15:00 Bayesian Sparsification of Neural Networks  
15:30 --- Break ---
16:00 Introduction into the 2nd coopetition - Artem Maevskiy (National Research University Higher School of Economics (RU))  
16:30
Guest lectures (until 18:00)
12:00 --- Break ---
12:30
Section 4. Generative models and networks - Vladislav Belavin (Yandex School of Data Analysis (RU)) (until 13:00)
13:00
Section 4. Generative models and networks - Vladislav Belavin (Yandex School of Data Analysis (RU)) (until 13:30)
13:30 --- Lunch ---
14:30
Section 4. Generative models and networks - Vladislav Belavin (Yandex School of Data Analysis (RU)) (until 15:00)
15:00
Section 4. Generative models and networks - Vladislav Belavin (Yandex School of Data Analysis (RU)) (until 15:30)
15:30 --- Break ---
16:00
Guest lectures (until 17:30)
12:00
Section 4. Generative models and networks - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 13:00)
12:00 Advanced GANs  
12:30 Seminar: Advanced GANs  
13:00 --- Lunch ---
14:00
Section 4. Generative models and networks - Artem Ryzhikov (National Research University Higher School of Economics (RU)) (until 15:00)
14:00 Flow models  
14:30 Seminar: Flow models  
15:00 --- Break ---
15:30
Section 4. Generative models and networks (until 16:30)
15:30 Invertible Generative Models  
16:00 Seminar: Invertible Generative Practice  
16:30 --- Break ---
17:00
Guest lectures (until 18:30)
12:00
Guest lectures (until 13:30)
12:00
Section 5. Advanced Optimization Methods - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 13:00)
12:00 BO-GP and friends  
12:30 Seminar: BO-GP and friends  
13:00 --- Lunch ---
14:00
Guest lectures (until 15:30)
15:30 --- Break ---
16:00
Socialization (until 17:00)
12:30 --- Lunch ---
13:30
Section X (until 14:30)
14:30 --- Break ---
15:00
Guest lectures - Michael Aaron Kagan (SLAC National Accelerator Laboratory (US)) (until 16:30)
16:30 --- Break ---
17:00 Guest Lecture - Dr Michela Paganini (Facebook AI Research)  
12:00
Guest lectures (until 13:30)
13:30 --- Lunch ---
14:30 --- Break ---
16:00
Guest lectures (until 17:30)
16:00 --- Lunch ---
13:00 Closing words - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))  
13:30 --- Lunch ---
14:30
Socialization (until 16:30)
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