
Machine learning proliferates in particle physics - qubitcoder
https://www.symmetrymagazine.org/article/machine-learning-proliferates-in-particle-physics
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buboard
"proliferates" ? skepticism? Afaik, people in CERN have been using neural nets
to identify trajectories at least since the 80s.

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xvilka
Exactly! They basically invented modern big data/data science. ROOT[1] is one
of the oldest statistical frameworks after all. And they have machine learning
in it too[2][3].

[1] [https://root.cern.ch/](https://root.cern.ch/)

[2] [https://root.cern.ch/tmva](https://root.cern.ch/tmva)

[3]
[http://iopscience.iop.org/article/10.1088/1742-6596/898/7/07...](http://iopscience.iop.org/article/10.1088/1742-6596/898/7/072046/pdf)

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xvilka
Note also, they are working heavily on ROOT 7[1], which will do some refactor,
not sure probably even better ML/DL support. Not sure why did they target
c++14 instead of c++17 though.

[1] [https://root.cern.ch/root-7](https://root.cern.ch/root-7)

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tpaschalis
The comments of buboard and xvilka are _on point_.

One thing I'd add though, is that physicists still have a healthy amount of
skepticism on ML/NN. They don't like the "black box" approach, where the
algorithm is regarded to "provide" the truth, but we're required to fully
understand the math behind any implementation, as well as to be able to answer
deeper questions on the results we're acquiring.

Background : I'm completing my master in Particle Physics, and have had the
opportunity to work along these kinds of people. They have wrestled their
entire careers with enormous amounts of data, create new solutions to problems
the industry had not even formulated, and keep themselves on the forefront of
Statistics and ML.

I feel that the things I've learned by trotting along grey-haired old-school
Unix wizards could not be replicated by any courses, bootcamps or manuals.

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abcininin
I wish there were concrete examples of how machine learning is being used.

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davesque
Pretty broad but, from one section in the article, sounds like they're using
convolutional layers in their networks?

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thoughtstheseus
Check out the podcast Linear Digressions, one of the hosts Katie went from
physics to data science/ML work.

