activity
20192026
most citedNeural network interpretation using descrambler groups

33 citations · 34 across the 6 of their papers we have counts for

collaborators

6 papers

hep-ex2026

A method for luminosity determination based on real-time hit reconstruction with the LHCb silicon pixel detector

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb +1177

The data acquisition system of the upgraded LHCb experiment includes the fast reconstruction of all hits in the vertex locator (VELO) pixel detector at the beam-crossing rate of 40…

hep-ex2026

Search for decays at the LHCb experiment with Run 2 data

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb +1188

A search for the lepton-flavour-violating decay is carried out using data collected by the LHCb experiment between 2016 and 2018 in proton-proton collisions at t…

hep-ex2026

Observation of the decay

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb +1184

The first observation of the decay is reported using proton-proton collision data recorded with the LHCb detector correspo…

hep-ex2026

Observation of violation in decays

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb +1172

The time-dependent asymmetry in decays is measured using proton-proton collision data corresponding to an integrated luminosity o…

hep-ex2025★ 1 cited

Measurement of the branching fraction of the decay and isospin asymmetry of decays

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb +1193

This paper describes a measurement of the branching fraction using data collected with the LHCb experiment in proton-proton collisions from 2016 to 2018. The datase…

eess.SP2019★ 33 cited

Neural network interpretation using descrambler groups

Jake L. Amey, Jake Keeley, Tajwar Choudhury +1

The lack of interpretability and trust is a much-criticised feature of deep neural networks. In fully connected nets, the signalling between inner layers is scrambled because backp…