Reading material

Books

A very nice and gentle introduction (based on TensorFlow and Keras) is provided in the textbook Deep Learning for Physics Research by Martin Erdmann, Jonas Glombitza, Gregor Kasieczka, and Uwe Klemradt.

https://worldscientific.com/worldscibooks/10.1142/12294worldscientific.com

You can find the excercises to the book (for free) here:

InformationDeep Learning for Physics Research

Papers

Eur. Phys. J. C 79 (2019): ATLAS b-jet identification performance and efficiency measurement with tt events in pp collisions at √s = 13 TeV

ATLAS $b$-jet identification performance and efficiency measurement with $t\bar{t}$ events in $pp$ collisions at $\sqrt{s}=13$ TeVatlas.web.cern.ch

ATL-PHYS-PUB-2020-014: Deep Sets based Neural Networks for Impact Parameter Flavour Tagging in ATLAS

Deep Sets based Neural Networks for Impact Parameter Flavour Tagging in ATLASatlas.web.cern.ch

ATL-PHYS-PUB-2017-010: Variable Radius, Exclusive-kT, and Center-of-Mass Subjet Reconstruction for Higgs(→bb) Tagging in ATLAS

Variable Radius, Exclusive-k$_{T}$, and Center-of-Mass Subjet Reconstruction for Higgs($\rightarrow b\bar{b}$) Tagging in ATLASatlas.web.cern.ch

Presentations

Overview of flavour tagging algorithms in ATLAS

2MB

FTAG-summie-overview.pdf

PDF

Open