Exploring end-to-end deep learning applications for event classification at cms

HIGHLIGHTS

• who: Andrews Michael et al. from the Department of Physics, Carnegie Mellon University, Pittsburgh, USA have published the article: Exploring End-to-end Deep Learning Applications for Event Classification at CMS, in the Journal: (JOURNAL)
• what: The authors demonstrate the power of this approach in the context of a physics search and offer solutions to some of the inherent challenges such as image construction image sparsity combining multiple sub-detectors and de-correlating the classifier from the search observable among others.

SUMMARY

Allowed for breakthroughs in computer vision and pattern_recognition with . . .

 



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