Conveners
Talk: Talks I
- Marcus Brueggen
Talk: Talks II
- There are no conveners in this block
Talk: Talks III
- Johannes Haller (CERN)
Talk: Talks IV
- Gregor Kasieczka (Hamburg University (DE))
When are two collider events similar? In this talk, I will answer this question by developing a metric between the radiation patterns of events. The metric is based on the well known earth mover’s distance, and intuitively is the minimum “work” required to rearrange the energy flow of one event into the other. With a metric in hand, I will discuss and demonstrate numerous tools for analyzing...
The Dark Matter Particle Explorer (DAMPE) is a space-borne particle detector and cosmic rays observatory in operations since 2015, equipped with alongside other instruments a deep calorimeter able to detect electrons up to an energy of 10 TeV and cosmic rays up to 100 TeV. The large proton and ion background in orbit requires a powerful electron identification method. We explore a neural...
Deep learning in particle physics often relies on imperfect simulations due to the lack of real labelled data, which risks learning mismodeling artifacts rather than the underlying physics. In this talk, I discuss the prospects for training classifiers directly on collider data using mixed samples, drawing from techniques in weak supervision and topic modeling. Using the example of quark...
Deep learning has shown a promising future in physics’ data analysis and is anticipated to revolutionize LHC discoveries.
Designing an optimal algorithm may seem to be the most challenging task in machine learning progress especially in HEP due to the high dimensionality and extreme complexity of the data.
Physical knowledge can be employed in designing and modifying of the algorithm’s...
