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2020 – today
- 2024
[i11]Andris Huang, Yash Melkani, Paolo Calafiura, Alina Lazar, Daniel Thomas Murnane, Minh-Tuan Pham, Xiangyang Ju:
A Language Model for Particle Tracking. CoRR abs/2402.10239 (2024)- 2023
- [i10]Ryan Liu
, Paolo Calafiura, Steven Farrell, Xiangyang Ju, Daniel Thomas Murnane, Tuan Minh Pham:
Hierarchical Graph Neural Networks for Particle Track Reconstruction. CoRR abs/2303.01640 (2023) - [i9]Daniel Murnane, Savannah Thais, Ameya Thete:
Equivariant Graph Neural Networks for Charged Particle Tracking. CoRR abs/2304.05293 (2023) - [i8]Daniel Murnane:
Graph Structure from Point Clouds: Geometric Attention is All You Need. CoRR abs/2307.16662 (2023) - [i7]Savannah Thais, Daniel Murnane:
Equivariance Is Not All You Need: Characterizing the Utility of Equivariant Graph Neural Networks for Particle Physics Tasks. CoRR abs/2311.03094 (2023) - 2022
- [i6]Daniel Murnane, Savannah Thais, Jason Wong:
Semi-Equivariant GNN Architectures for Jet Tagging. CoRR abs/2202.06941 (2022) - [i5]Alexander Bogatskiy, Sanmay Ganguly, Thomas Kipf, Risi Kondor, David W. Miller, Daniel Murnane, Jan T. Offermann, Mariel Pettee, Phiala E. Shanahan, Chase Shimmin, Savannah Thais:
Symmetry Group Equivariant Architectures for Physics. CoRR abs/2203.06153 (2022) - [i4]Savannah Thais, Paolo Calafiura, Grigorios Chachamis, Gage DeZoort, Javier M. Duarte, Sanmay Ganguly, Michael Kagan, Daniel Murnane, Mark S. Neubauer, Kazuhiro Terao:
Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges. CoRR abs/2203.12852 (2022) - [i3]Xiangyang Ju, Yunsong Wang, Daniel Murnane, Nicholas Choma, Steven Farrell, Paolo Calafiura:
Benchmarking GPU and TPU Performance with Graph Neural Networks. CoRR abs/2210.12247 (2022) - 2021
- [i2]Xiangyang Ju, Daniel Murnane, Paolo Calafiura, Nicholas Choma, Sean Conlon, Steven Farrell, Yaoyuan Xu, Maria Spiropulu, Jean-Roch Vlimant, Adam Aurisano, Jeremy Hewes, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Markus Atkinson, Mark S. Neubauer, Gage DeZoort, Savannah Thais, Aditi Chauhan, Alex Schuy, Shih-Chieh Hsu, Alexandra Ballow, Alina Lazar:
Physics and Computing Performance of the Exa.TrkX TrackML Pipeline. CoRR abs/2103.06995 (2021) - 2020
- [i1]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 L. Usher:
Track Seeding and Labelling with Embedded-space Graph Neural Networks. CoRR abs/2007.00149 (2020)
Coauthor Index
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