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Man, when I was doing my PhD at CERN the most far out thing that we were generally allowed to use was boosted decision trees :) getting anything other than that approved for any Higgs-related analysis was… not a thing.
Man, when I was doing my PhD at CERN the most far out thing that we were generally allowed to use was boosted decision trees :) getting anything other than that approved for any Higgs-related analysis was… not a thing.
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Using neural nets for signal background separation was pretty standard in ~2012 when the Higgs discovery was published. Was also pretty standard for CDF + DZero papers that came out before the LHC turned on. https://arxiv.org/abs/1207.7214 - The original ATLAS Higgs discovery paper uses neural nets to identify photons. It also uses a neural net b-tagger to improve the H->WW signal to noise ratio. https://arxiv.org/abs/1303.0763 - used neural nets extra tt+jets noise https://arxiv.org/abs/1503.05066 - used neural nets for signal/background separation.
You needed approval to try different methods for data analysis?
We surely came a long way since then. I recently finished my master thesis on self-supervised foundation models for jets :)
It was certainly dogma, but adventurous students were known to have activated the MLP models in TMVA ;)
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