Sixth Machine Learning in High Energy Physics Summer School 2020

from Thursday, July 16, 2020 (9:00 AM) to Thursday, July 30, 2020 (8:30 PM)
Zoom

        : Sessions
    /     : Talks
        : Breaks
Jul 16, 2020
Jul 17, 2020
Jul 18, 2020
Jul 19, 2020
Jul 20, 2020
Jul 21, 2020
Jul 22, 2020
Jul 23, 2020
Jul 24, 2020
Jul 25, 2020
Jul 27, 2020
Jul 28, 2020
Jul 29, 2020
Jul 30, 2020
AM
9:00 AM Welcome, opening words - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   ()
9:30 AM Practice. Getting familiar with school infrastructure - Vladislav Belavin (Yandex School of Data Analysis (RU)) Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   ()
10:00 AM --- Break ---
10:15 AM Intro into Machine Intelligence - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   ()
11:30 AM
Section 1. Introduction into ML - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 12:45 PM) ()
11:30 AM Introduction into supervised learning - Artem Maevskiy (National Research University Higher School of Economics (RU))   ()
12:00 PM Seminar: Data Handling in Python - Artem Maevskiy (National Research University Higher School of Economics (RU))   ()
9:00 AM
Section 1. Introduction into ML - Mikhail Hushchyn (Yandex School of Data Analysis (RU)) (until 10:00 AM) ()
9:00 AM Quality Metrics-1 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))   ()
9:30 AM Seminar: Quality Metrics-1   ()
10:00 AM --- Break ---
10:30 AM
Section 1. Introduction into ML - Mikhail Hushchyn (Yandex School of Data Analysis (RU)) (until 11:30 AM) ()
10:30 AM Quality Metrics-2 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))   ()
11:00 AM Seminar: Quality Metrics-2 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))   ()
11:30 AM --- Break ---
9:00 AM
Section 1. Introduction into ML - Mikhail Hushchyn (Yandex School of Data Analysis (RU)) (until 10:00 AM) ()
9:00 AM Useful hacks - Mikhail Hushchyn (Yandex School of Data Analysis (RU))   ()
9:30 AM Seminar: Useful hacks. - Mikhail Hushchyn (Yandex School of Data Analysis (RU))   ()
10:00 AM --- Break ---
10:30 AM
Section 1. Introduction into ML - Mikhail Hushchyn (Yandex School of Data Analysis (RU)) (until 11:30 AM) ()
10:30 AM Clustering-1 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))   ()
11:00 AM Seminar: Clustering-1 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))   ()
11:30 AM --- Break ---
9:00 AM --- Sunday ---
9:00 AM
Section 2. Introduction into Neural Networks - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 10:00 AM) ()
9:00 AM Intro to NN - Artem Maevskiy (National Research University Higher School of Economics (RU))   ()
9:20 AM Seminar: Intro to NN - Artem Maevskiy (National Research University Higher School of Economics (RU))   ()
10:00 AM --- Break ---
10:30 AM
Section 2. Introduction into Neural Networks - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)) (until 11:30 AM) ()
10:30 AM Intro to Pytorch - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   ()
11:00 AM Seminar: Pytorch practice - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   ()
11:30 AM --- Break ---
9:00 AM
Section 2. Introduction to Neural Nets - Artem Ryzhikov (National Research University Higher School of Economics (RU)) (until 10:00 AM) ()
9:00 AM Autoregressive networks-2   ()
9:30 AM Seminar: Autoregressive networks-2   ()
10:00 AM --- Break ---
10:30 AM
Section 2. Introduction to Neural Nets - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 11:30 AM) ()
10:30 AM Network architectures: tips and tricks   ()
11:10 AM Seminar: Practice   ()
11:30 AM --- Break ---
9:00 AM
Section 3. Bayesian Deep Learning - Ekaterina Lobacheva (until 10:00 AM) ()
9:00 AM Variational Inference   ()
9:30 AM Seminar: Variational Inference   ()
10:00 AM --- Break ---
10:30 AM
Section 3. Bayesian Deep Learning - Nadya Chirkova (until 11:30 AM) ()
11:30 AM --- Break ---
9:00 AM
Section 3. Bayesian Deep Learning (until 10:00 AM) ()
9:00 AM VAE   ()
9:30 AM Seminar: VAE   ()
10:00 AM
Section 3. Bayesian Deep Learning - Alexei Struminsky (Space Research Institute) (until 10:30 AM) ()
10:30 AM --- Break ---
11:00 AM
Section 4. Generative models and networks - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 11:30 AM) ()
11:30 AM
Section 4. Generative models and networks - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 12:00 PM) ()
9:00 AM
Section 4. Generative models and networks - Artem Ryzhikov (National Research University Higher School of Economics (RU)) (until 10:00 AM) ()
9:00 AM Autoencoders   ()
9:30 AM Seminar: Practice on AE   ()
10:00 AM --- Break ---
10:30 AM
Section 4. Generative models and networks - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 11:30 AM) ()
10:30 AM GANs   ()
11:00 AM Seminar: GANs   ()
11:30 AM --- Break ---
9:00 AM
Section 5. Advanced Optimization Methods - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 10:00 AM) ()
9:00 AM Introduction to black-box optimization   ()
9:30 AM Seminar: Introduction to black-box optimization   ()
10:00 AM --- Break ---
10:30 AM
Section 5. Advanced Optimization Methods -Mr Vladislav Belavin (Yandex School of Data Analysis (RU)) (until 11:30 AM) ()
11:30 AM --- Break ---
9:00 AM
Section 5. Advanced Optimization Methods - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 10:00 AM) ()
9:00 AM Bayesian Optimization   ()
9:30 AM Seminar: Bayesian Optimization   ()
10:00 AM --- Break ---
10:30 AM
Section 5. Advanced Optimization Methods - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 11:30 AM) ()
10:30 AM BO-GP and friends   ()
11:00 AM Seminar: BO-GP and friends   ()
11:30 AM --- Break ---
9:00 AM
Section X - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 10:00 AM) ()
9:00 AM Learning to pivot   ()
9:20 AM Seminar: Learning to pivot   ()
10:00 AM --- Break ---
10:30 AM
Section X (until 12:30 PM) ()
9:00 AM
Section X - Denis Derkach (National Research University Higher School of Economics (RU)) (until 10:00 AM) ()
10:00 AM --- Break ---
10:30 AM
Section X - Denis Derkach (National Research University Higher School of Economics (RU)) (until 11:30 AM) ()
11:30 AM --- Break ---
9:00 AM
Guest lectures (until 10:30 AM) ()
10:30 AM --- Break ---
11:30 AM
Socialization (until 1:00 PM) ()
PM
12:45 PM --- Lunch ---
1:30 PM
Section 1. Introduction into ML - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 2:30 PM) ()
1:30 PM Linear Regression - Artem Maevskiy (National Research University Higher School of Economics (RU))   ()
2:00 PM Seminar - Artem Maevskiy (National Research University Higher School of Economics (RU))   ()
2:30 PM --- Break ---
3:00 PM
Section 1. Introduction into ML - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 4:00 PM) ()
3:00 PM Logistic regression-1 - Artem Maevskiy (National Research University Higher School of Economics (RU))   ()
3:30 PM Seminar   ()
4:00 PM --- Break ---
4:30 PM
Section 1. Introduction into ML - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 5:30 PM) ()
4:30 PM Logistic regression-2 - Artem Maevskiy (National Research University Higher School of Economics (RU))   ()
5:00 PM Seminar - Artem Maevskiy (National Research University Higher School of Economics (RU))   ()
12:00 PM
Section 1. Introduction into ML - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 1:00 PM) ()
12:00 PM Decision trees-1 - Mr Nikita Kazeev (Yandex School of Data Analysis (RU))   ()
12:30 PM Seminar: Decision trees-1 - Nikita Kazeev (Yandex School of Data Analysis (RU))   ()
1:00 PM --- Lunch ---
2:00 PM
Section 1. Introduction into ML - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 3:00 PM) ()
2:00 PM Ensembles-1 - Nikita Kazeev (Yandex School of Data Analysis (RU))   ()
2:30 PM Seminar: Ensembles-1 - Nikita Kazeev (Yandex School of Data Analysis (RU))   ()
3:00 PM --- Break ---
3:30 PM
Section 1. Introduction into ML - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 4:30 PM) ()
3:30 PM Ensembles-2 - Nikita Kazeev (Yandex School of Data Analysis (RU))   ()
4:00 PM Seminar: Ensembles-2 - Nikita Kazeev (Yandex School of Data Analysis (RU))   ()
4:30 PM Coopetition introduction (1) - Mr Nikita Kazeev (Yandex School of Data Analysis (RU))   ()
5:00 PM --- Break ---
5:30 PM
Socialization (until 6:30 PM) ()
12:00 PM
Section 1. Introduction into ML - Mikhail Hushchyn (Yandex School of Data Analysis (RU)) (until 1:00 PM) ()
12:00 PM Clustering-2 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))   ()
12:30 PM Seminar: Clustering-2 - Mikhail Hushchyn (Yandex School of Data Analysis (RU))   ()
12:00 PM
Section 2. Introduction into Neural Networks - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)) (until 1:00 PM) ()
12:00 PM CNN - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   ()
12:30 PM Seminar: CNN - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   ()
1:00 PM --- Lunch ---
2:00 PM
Section 2. Introduction into Neural Networks - Artem Maevskiy (National Research University Higher School of Economics (RU)) (until 3:00 PM) ()
2:00 PM Network regularization   ()
2:30 PM Seminar: Network regularization   ()
3:00 PM --- Break ---
3:30 PM
Section 2. Introduction to Neural Nets - Artem Ryzhikov (National Research University Higher School of Economics (RU)) (until 4:30 PM) ()
3:30 PM Autoregressive networks   ()
4:00 PM Seminar: Autoregressive networks   ()
4:30 PM --- Break ---
5:00 PM
Guest lectures - Tommaso Dorigo (Universita e INFN, Padova (IT)) (until 6:30 PM) ()
12:00 PM
Section 3. Bayesian Deep Learning - Ekaterina Lobacheva (until 1:00 PM) ()
12:00 PM Intro   ()
12:30 PM Seminar: Intro   ()
1:00 PM --- Lunch ---
2:00 PM
Section 3. Bayesian Deep Learning - Ekaterina Lobacheva (until 3:00 PM) ()
2:00 PM Full Bayesian Inference   ()
2:30 PM Seminar: Full Bayesian Inference   ()
3:00 PM --- Break ---
3:30 PM
Section 3. Bayesian Deep Learning - Nadya Chirkova (until 4:00 PM) ()
4:00 PM --- Break ---
4:30 PM
Guest lectures (until 6:00 PM) ()
12:00 PM
Section 3. Bayesian Deep Learning - Nadya Chirkova (until 1:30 PM) ()
12:00 PM Bayesian Neural Networks - Introduction   ()
12:30 PM Bayesian Neural Networks - Training   ()
1:30 PM --- Lunch ---
2:30 PM
Section 3. Bayesian Deep Learning - Nadya Chirkova (until 3:30 PM) ()
2:30 PM Seminar: Bayesian Neural Networks - Training   ()
3:00 PM Bayesian Sparsification of Neural Networks   ()
3:30 PM --- Break ---
4:00 PM Introduction into the 2nd coopetition - Artem Maevskiy (National Research University Higher School of Economics (RU))   ()
4:30 PM
Guest lectures (until 6:00 PM) ()
12:00 PM --- Break ---
12:30 PM
Section 4. Generative models and networks - Vladislav Belavin (Yandex School of Data Analysis (RU)) (until 1:00 PM) ()
1:00 PM
Section 4. Generative models and networks - Vladislav Belavin (Yandex School of Data Analysis (RU)) (until 1:30 PM) ()
1:30 PM --- Lunch ---
2:30 PM
Section 4. Generative models and networks - Vladislav Belavin (Yandex School of Data Analysis (RU)) (until 3:00 PM) ()
3:00 PM
Section 4. Generative models and networks - Vladislav Belavin (Yandex School of Data Analysis (RU)) (until 3:30 PM) ()
3:30 PM --- Break ---
4:00 PM
Guest lectures (until 5:30 PM) ()
12:00 PM
Section 4. Generative models and networks - Nikita Kazeev (Yandex School of Data Analysis (RU)) (until 1:00 PM) ()
12:00 PM Advanced GANs   ()
12:30 PM Seminar: Advanced GANs   ()
1:00 PM --- Lunch ---
2:00 PM
Section 4. Generative models and networks - Artem Ryzhikov (National Research University Higher School of Economics (RU)) (until 3:00 PM) ()
2:00 PM Flow models   ()
2:30 PM Seminar: Flow models   ()
3:00 PM --- Break ---
3:30 PM
Section 4. Generative models and networks (until 4:30 PM) ()
3:30 PM Invertible Generative Models   ()
4:00 PM Seminar: Invertible Generative Practice   ()
4:30 PM --- Break ---
5:00 PM
Guest lectures (until 6:30 PM) ()
12:00 PM
Guest lectures (until 1:30 PM) ()
12:00 PM
Section 5. Advanced Optimization Methods - Maxim Borisyak (Yandex School of Data Analysis (RU)) (until 1:00 PM) ()
12:00 PM BO-GP and friends   ()
12:30 PM Seminar: BO-GP and friends   ()
1:00 PM --- Lunch ---
2:00 PM
Guest lectures (until 3:30 PM) ()
3:30 PM --- Break ---
4:00 PM
Socialization (until 5:00 PM) ()
12:30 PM --- Lunch ---
1:30 PM
Section X (until 2:30 PM) ()
2:30 PM --- Break ---
3:00 PM
Guest lectures - Michael Aaron Kagan (SLAC National Accelerator Laboratory (US)) (until 4:30 PM) ()
4:30 PM --- Break ---
5:00 PM Guest Lecture - Dr Michela Paganini (Facebook AI Research)   ()
12:00 PM
Guest lectures (until 1:30 PM) ()
1:30 PM --- Lunch ---
2:30 PM --- Break ---
4:00 PM
Guest lectures (until 5:30 PM) ()
4:00 PM --- Lunch ---
1:00 PM Closing words - Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))   ()
1:30 PM --- Lunch ---
2:30 PM
Socialization (until 4:30 PM) ()