Machine Learning for High Energy Physics - a mini course

Contribution List

11. Registration

2/4/19, 9:00 AM

13. Welcome

Ben Kilminster (Universitaet Zuerich (CH))

2/4/19, 9:30 AM

12. Introduction

Thea Aarrestad (Universitaet Zuerich (CH))

2/4/19, 9:35 AM

1. Basics of neural networks and training

Gregor Kasieczka (Hamburg University (DE))

2/4/19, 9:45 AM

2. Convolutional networks

Gregor Kasieczka (Hamburg University (DE))

2/4/19, 11:00 AM

3. Recurrent architectures

Gregor Kasieczka (Hamburg University (DE))

2/4/19, 2:00 PM

4. Combining Physics and Deep Learning

Gregor Kasieczka (Hamburg University (DE))

2/4/19, 3:15 PM

10. Invited evening talk: Machine Learning for HL-LHC

Jennifer Ngadiuba (CERN)

2/4/19, 5:00 PM

5. Systematic Uncertainties and Learning from Data

Gregor Kasieczka (Hamburg University (DE))

2/5/19, 9:30 AM

6. Generative Networks and Understanding network decisions

Gregor Kasieczka (Hamburg University (DE))

2/5/19, 11:00 AM

7. Hands-on

Gregor Kasieczka (Hamburg University (DE))

2/5/19, 2:00 PM

8. Hands-on

Gregor Kasieczka (Hamburg University (DE))

2/5/19, 3:15 PM

9. Scaling up TensorFlow on Accelerators

Marvin Ritter (Google AI)

2/5/19, 5:00 PM