297 citations · 1k across the 24 of their papers we have counts for
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Interpreting Transformers for Jet Tagging
Aaron Wang, Abhijith Gandrakota, Jennifer Ngadiuba +4
Machine learning (ML) algorithms, particularly attention-based transformer models, have become indispensable for analyzing the vast data generated by particle physics experiments l…
Expected Tracking Performance of the ATLAS Inner Tracker at the High-Luminosity LHC
ATLAS Collaboration
The high-luminosity phase of LHC operations (HL-LHC), will feature a large increase in simultaneous proton-proton interactions per bunch crossing up to 200, compared with a typical…
Graph Neural Network-based Tracking as a Service
Haoran Zhao, Andrew Naylor, Shih-Chieh Hsu +8
Recent studies have shown promising results for track finding in dense environments using Graph Neural Network (GNN)-based algorithms. However, GNN-based track finding is computati…
FPGA Deployment of LFADS for Real-time Neuroscience Experiments
Xiaohan Liu, ChiJui Chen, YanLun Huang +6
Large-scale recordings of neural activity are providing new opportunities to study neural population dynamics. A powerful method for analyzing such high-dimensional measurements is…
Ultra Fast Transformers on FPGAs for Particle Physics Experiments
Zhixing Jiang, Dennis Yin, Elham E Khoda +6
This work introduces a highly efficient implementation of the transformer architecture on a Field-Programmable Gate Array (FPGA) by using the \texttt{hls4ml} tool. Given the demons…