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White paper organization #6
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I suppose we might have:
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Thanks for the list @tdorigo! A comment:
Not sure if these are accurate subcategories -- neither of neos or inferno are classifiers right? That to me implies training with a classification-based objective, which each approach explicitly tries to circumvent. A more accurate picture in my mind would be one of optimal summary statistics, or even in some sense optimal event selection. Optimising a differentiable cutflow could also come into play there. |
I agree, but I would make the list of topics and proposed solutions correspond as closely as possible to the HEP use cases of interest, rather than display a list of tools. |
Just for the sake of keeping track of the timescale, me and @lukasheinrich will try to publish something on neos in the next month or so before working on this, which will also allow us to cite it :) |
Good, always cite yourself. If you don't, why expect others to do the same? |
To help lay the groundwork for part 2, it might be useful to layout in part 1 a set of ideal specifications for the hows (e.g. modular, intuitive & accessible, and low hardware-requirements). Whilst we might have the specification in mind ourselves, this could be useful for getting early feedback from the community prior to writing part 2, in case we miss anything, or certain things are redundant. |
We agreed at the kick off meeting to form a white paper that highlights this fairly new analysis paradigm for people new to it.
I think this may end up becoming two papers: the ‘whys’ (initial motivations, existing efforts) and the ‘hows’ (evaluation and comparisons of the methods implemented with common tools in a realistic setting).
What should we include (in paper 1?) :)
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