3rd IML Machine Learning Workshop

Session

Tutorials

18 Apr 2019, 09:00

500/1-001 - Main Auditorium (CERN)

Conveners

Tutorials: Part 1

• Lorenzo Moneta (CERN)
• Rudiger Haake (Yale University (US))

Tutorials: Part 2

• David Rousseau (LAL-Orsay, FR)
• Rudiger Haake (Yale University (US))

4. Introduction to the basics of deep learning

Yannik Alexander Rath (RWTH Aachen University (DE))

18/04/2019, 09:00

6. Physics inspired Autonomous Feature Engineering

Marcel Rieger (RWTH Aachen University (DE))

18/04/2019, 11:00

33. Traditional approach to network architecture optimisation

Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))

18/04/2019, 12:00

34. Differentiable architecture search

Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))

18/04/2019, 12:30

35. Bayesian approach to network design

Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))

18/04/2019, 15:00

36. Bayesian dropout explanation and examples

Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))

18/04/2019, 15:30

5. Advanced Generative Adversarial Network Techniques

Jonas Glombitza (Rheinisch-Westfaelische Tech. Hoch. (DE))

18/04/2019, 16:45

7. Tutorial, part 1

8. Tutorial, part 2