[Triumf-seminars] TRIUMF Colloquium today at 14:00

[TRIUMF Seminars]

Date/Time: Thu 2022-04-07 at 14:00

Location:  Remote              

Speaker:   Benjamin Nachman (LBNL)

Title:     What can deep learning teach us about particle physics?

Abstract: Despite extensive theoretical motivation for physics beyond the Standard Model (BSM) of particle physics, searches at the Large Hadron Collider (LHC) and elsewhere have found no convincing evidence for BSM physics. Therefore, it is essential to broaden the sensitivity of the search program to include unexpected scenarios.  Machine Learning (ML) gives us hyper-variate vision to identify BSM signatures in ways that were not previously possible.  However, traditional ML techniques require us to provide labeled training data in order to teach them how to look for something "new".  I will introduce an innovative and exciting research direction called anomaly detection where ML techniques can be applied to unlabeled data in order to teach us how to look for something genuinely new (i.e., unexpected).  To illustrate the power of these methods, I will use examples from collider physics, though many of the techniques likely have broader applicability.

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Remote Connection Link:
https://ubc.zoom.us/j/69420340890?pwd=T1Qyd1Zmckw0Umk5dGdiSUk4K2lTUT09

Meeting ID: 694 2034 0890
Passcode: 480381



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