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Machine Learning for High Energy Physics - a mini course

4–5 Feb 2019

University of Zurich, Campus Irchel

Europe/Zurich timezone

Thea Årrestad

Contribution List

11. Registration

04/02/2019, 09:00

Ben Kilminster (Universitaet Zuerich (CH))

04/02/2019, 09:30

12. Introduction

Thea Aarrestad (Universitaet Zuerich (CH))

04/02/2019, 09:35

1. Basics of neural networks and training

Gregor Kasieczka (Hamburg University (DE))

04/02/2019, 09:45

2. Convolutional networks

Gregor Kasieczka (Hamburg University (DE))

04/02/2019, 11:00

3. Recurrent architectures

Gregor Kasieczka (Hamburg University (DE))

04/02/2019, 14:00

4. Combining Physics and Deep Learning

Gregor Kasieczka (Hamburg University (DE))

04/02/2019, 15:15

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

Jennifer Ngadiuba (CERN)

04/02/2019, 17:00

5. Systematic Uncertainties and Learning from Data

Gregor Kasieczka (Hamburg University (DE))

05/02/2019, 09:30

6. Generative Networks and Understanding network decisions

Gregor Kasieczka (Hamburg University (DE))

05/02/2019, 11:00

Gregor Kasieczka (Hamburg University (DE))

05/02/2019, 14:00

Gregor Kasieczka (Hamburg University (DE))

05/02/2019, 15:15

9. Scaling up TensorFlow on Accelerators

Marvin Ritter (Google AI)

05/02/2019, 17:00