ICALEPCS 2021: 2nd Data Science and Machine Learning Workshop

Session

Overview Session

15 Oct 2021, 12:10

Remote

4. Machine learning for accelerators: a physicist approach

Pierre Schnizer (BESSY)

15/10/2021, 12:10

Machine learning has become ubiquitous today as a bracket for similar but different concepts statistical learning, neural networks, and reinforcement learning. These different approaches allow tackling a wide range of problems: deriving complex parameter sets from stochastic data, discover or simplify complex relationships, substitute diagnostics, e.g., particular beam destructive ones.
This...

5. AI/ML Operational challenges at SLAC's accelerators & Collaborating Facilities

Auralee Linscott Edelen

15/10/2021, 12:45

Particle accelerators are used in a wide array of medical, industrial, and scientific applications, ranging from cancer treatment to understanding fundamental laws of physics. While each of these applications brings with them different operational requirements, a common challenge concerns how to optimally adjust controllable settings of the accelerator to obtain the desired beam...

6. ML and optimization algorithms for CERN accelerators

Verena Kain (CERN)

15/10/2021, 13:20

The presentation will go through the recent projects in the field that are regularly shared at the CERN ML and Data Analytics community forum. The current status of the development and the results obtained so far will be highlighted.

7. Discussion