PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant
Aggregator Network for Particle Physics

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PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant Aggregator Network for Particle Physics

1 November 2022

Timothy Hoffman

David W. Miller

Jan T. Offermann

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Papers citing "PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant Aggregator Network for Particle Physics"

18 / 18 papers shown

Title
Lorentz Local Canonicalization: How to Make Any Network Lorentz-Equivariant Jonas Spinner Luigi Favaro Peter Lippmann Sebastian Pitz Gerrit Gerhartz Tilman Plehn Fred Hamprecht AI4CE 32 1 0 26 May 2025
Learning symmetries in datasets Veronica Sanz DRL 55 0 0 07 Apr 2025
A Lorentz-Equivariant Transformer for All of the LHC Johann Brehmer Victor Bresó P. D. Haan Tilman Plehn Huilin Qu Jonas Spinner Jesse Thaler BDL 106 18 0 01 Nov 2024
Does equivariance matter at scale? Johann Brehmer S. Behrends P. D. Haan Taco S. Cohen 108 15 0 30 Oct 2024
Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics Jonas Spinner Victor Bresó P. D. Haan Tilman Plehn Jesse Thaler Johann Brehmer AI4CE 96 19 0 23 May 2024
Moments of Clarity: Streamlining Latent Spaces in Machine Learning using Moment Pooling Rikab Gambhir Athis Osathapan Jesse Thaler 84 3 0 13 Mar 2024
Clifford-Steerable Convolutional Neural Networks Maksim Zhdanov David Ruhe Maurice Weiler Ana Lucic Johannes Brandstetter Patrick Forré 126 15 0 22 Feb 2024
Ultrafast jet classification on FPGAs for the HL-LHC Patrick Odagiu Zhiqiang Que Javier Mauricio Duarte J. Haller Gregor Kasieczka ... Arpita Seksaria S. Summers A. Sznajder A. Tapper Thea Klæboe Årrestad 65 3 0 02 Feb 2024
$$\mathbb{Z}_2\times \mathbb{Z}_2$ Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks$ $\mathbb{Z}_2\times \mathbb{Z}_2$ Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks Zhongtian Dong Marçal Comajoan Cara Gopal Ramesh Dahale Roy T. Forestano S. Gleyzer ... Kyoungchul Kong Tom Magorsch Konstantin T. Matchev Katia Matcheva Eyup B. Unlu 92 5 0 30 Nov 2023
Equivariance Is Not All You Need: Characterizing the Utility of Equivariant Graph Neural Networks for Particle Physics Tasks S. Thais D. Murnane AI4CE 77 5 0 06 Nov 2023
19 Parameters Is All You Need: Tiny Neural Networks for Particle Physics A. Bogatskiy Timothy Hoffman Jan T. Offermann 93 3 0 24 Oct 2023
A Geometric Insight into Equivariant Message Passing Neural Networks on Riemannian Manifolds Ilyes Batatia 51 0 0 16 Oct 2023
PCN: A Deep Learning Approach to Jet Tagging Utilizing Novel Graph Construction Methods and Chebyshev Graph Convolutions Yash Semlani Mihir Relan Krithik Ramesh GNN 103 3 0 12 Sep 2023
Reconstruction of Unstable Heavy Particles Using Deep Symmetry-Preserving Attention Networks M. Fenton Alexander Shmakov H. Okawa Yuji Li Ko-Yang Hsiao Shih-Chieh Hsu D. Whiteson Pierre Baldi 81 7 0 05 Sep 2023
Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds O. Melia Eric Jonas Rebecca Willett OOD 3DPC 75 3 0 27 Jul 2023
Anomalies, Representations, and Self-Supervision B. Dillon Luigi Favaro Friedrich Feiden Tanmoy Modak Tilman Plehn 70 10 0 11 Jan 2023
Feature Selection with Distance Correlation Ranit Das Gregor Kasieczka David Shih 68 14 0 30 Nov 2022
A Detailed Study of Interpretability of Deep Neural Network based Top Taggers Ayush Khot Mark S. Neubauer Avik Roy AAML 114 18 0 09 Oct 2022