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researcher

William Tepe

3 papers hereh-index 29 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • hep-ex3

identity via Semantic Scholar / OpenAlex

most citedProgress in developing a hybrid deep learning algorithm for identifying and locating primary vertices

3 citations · 6 across the 3 of their papers we have counts for

collaborators

3 papers

hep-ex2023★ 1 cited

Advances in developing deep neural networks for finding primary vertices in proton-proton collisions at the LHC

Simon Akar, Mohamed Elashri, Rocky Bala Garg +6

We are studying the use of deep neural networks (DNNs) to identify and locate primary vertices (PVs) in proton-proton collisions at the LHC. Earlier work focused on finding primary…

hep-ex2023★ 2 cited

Comparing and improving hybrid deep learning algorithms for identifying and locating primary vertices

Simon Akar, Michael Peters, Henry Schreiner +2

Using deep neural networks to identify and locate proton-proton collision points, or primary vertices, in LHCb has been studied for several years. Preliminary results demonstrated…

hep-ex2021★ 3 cited

Progress in developing a hybrid deep learning algorithm for identifying and locating primary vertices

Simon Akar, Gowtham Atluri, Thomas Boettcher +7

The locations of proton-proton collision points in LHC experiments are called primary vertices (PVs). Preliminary results of a hybrid deep learning algorithm for identifying and lo…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.