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Daniel Murnane

Lawrence Berkeley National Laboratory

Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges


Mar 25, 2022
Savannah Thais, Paolo Calafiura, Grigorios Chachamis, Gage DeZoort, Javier Duarte, Sanmay Ganguly, Michael Kagan, Daniel Murnane, Mark S. Neubauer, Kazuhiro Terao

* contribution to Snowmass 2021 

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Symmetry Group Equivariant Architectures for Physics


Mar 11, 2022
Alexander Bogatskiy, Sanmay Ganguly, Thomas Kipf, Risi Kondor, David W. Miller, Daniel Murnane, Jan T. Offermann, Mariel Pettee, Phiala Shanahan, Chase Shimmin, Savannah Thais

* Contribution to Snowmass 2021 

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Semi-Equivariant GNN Architectures for Jet Tagging


Feb 14, 2022
Daniel Murnane, Savannah Thais, Jason Wong

* Proceedings submission to ACAT2021 Conference. 9 pages 

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Physics and Computing Performance of the Exa.TrkX TrackML Pipeline


Mar 11, 2021
Xiangyang Ju, Daniel Murnane, Paolo Calafiura, Nicholas Choma, Sean Conlon, Steve Farrell, Yaoyuan Xu, Maria Spiropulu, Jean-Roch Vlimant, Adam Aurisano, Jeremy Hewes, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Markus Atkinson, Mark Neubauer, Gage DeZoort, Savannah Thais, Aditi Chauhan, Alex Schuy, Shih-Chieh Hsu, Alex Ballow, and Alina Lazar


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Track Seeding and Labelling with Embedded-space Graph Neural Networks


Jun 30, 2020
Nicholas Choma, Daniel Murnane, Xiangyang Ju, Paolo Calafiura, Sean Conlon, Steven Farrell, Prabhat, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Panagiotis Spentzouris, Jean-Roch Vlimant, Maria Spiropulu, Adam Aurisano, Jeremy Hewes, Aristeidis Tsaris, Kazuhiro Terao, Tracy Usher

* Proceedings submission in Connecting the Dots Workshop 2020, 10 pages 

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