744 citations · 6.5k across the 102 of their papers we have counts for
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physics.data-an2019★ 63 cited
FPGA-accelerated machine learning inference as a service for particle physics computing
Javier Duarte, Philip Harris, Scott Hauck +20
New heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting solutions with large pote…
physics.data-an2019★ 137 cited
Learning representations of irregular particle-detector geometry with distance-weighted graph networks
Shah Rukh Qasim, Jan Kieseler, Yutaro Iiyama +1
We explore the use of graph networks to deal with irregular-geometry detectors in the context of particle reconstruction. Thanks to their representation-learning capabilities, grap…