Lorentz Group Equivariant Neural Network for Particle Physics

8 June 2020

Papers citing "Lorentz Group Equivariant Neural Network for Particle Physics"

50 / 101 papers shown

Title
Permutation Equivariant Neural Networks for Symmetric Tensors Edward Pearce-Crump 48 0 0 14 Mar 2025
Generalization Bounds for Equivariant Networks on Markov Data Hui Li Zhiguo Wang Bohui Chen Li Sheng 29 0 0 01 Mar 2025
Learning Chern Numbers of Topological Insulators with Gauge Equivariant Neural Networks Longde Huang Oleksandr Balabanov H. Linander Mats Granath Daniel Persson Jan E. Gerken 38 0 0 24 Feb 2025
Effective Field Neural Network Xi Liu Yujun Zhao Chun Yu Wan Yang Zhang Junwei Liu AI4CE 38 0 0 24 Feb 2025
A group-theoretic framework for machine learning in hyperbolic spaces Vladimir Jaćimović 41 0 0 12 Jan 2025
Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding Jiajun Zhu Peihao Wang Ruisi Cai Jason D. Lee Pan Li Z. Wang KELM 38 1 0 03 Jan 2025
Enhancing generalization in high energy physics using white-box adversarial attacks Franck Rothen Samuel Klein Matthew Leigh T. Golling AAML 31 1 0 14 Nov 2024
Approximate Equivariance in Reinforcement Learning Jung Yeon Park Sujay Bhatt Sihan Zeng Lawson L. S. Wong Alec Koppel Sumitra Ganesh Robin Walters 34 1 0 06 Nov 2024
Optimal Equivariant Architectures from the Symmetries of Matrix-Element Likelihoods Daniel Maître Vishal S. Ngairangbam M. Spannowsky 29 4 0 24 Oct 2024
Towards Stable, Globally Expressive Graph Representations with Laplacian Eigenvectors Junru Zhou Cai Zhou Xiyuan Wang Pan Li Muhan Zhang 37 0 0 13 Oct 2024
Reinforcement Learning in Hyperbolic Spaces: Models and Experiments V. Jaćimović Zinaid Kapić Aladin Crnkić 22 0 0 12 Oct 2024
Equi-GSPR: Equivariant SE(3) Graph Network Model for Sparse Point Cloud Registration Xueyang Kang Zhaoliang Luan Kourosh Khoshelham Bing Wang 3DPC 34 0 0 08 Oct 2024
Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models Theo Putterman Derek Lim Yoav Gelberg Stefanie Jegelka Haggai Maron AI4CE 43 5 0 05 Oct 2024
Improving Equivariant Model Training via Constraint Relaxation Stefanos Pertigkiozoglou Evangelos Chatzipantazis Shubhendu Trivedi Kostas Daniilidis 39 4 0 23 Aug 2024
Optimal Symmetries in Binary Classification Vishal S. Ngairangbam M. Spannowsky 34 1 0 16 Aug 2024
Towards Understanding Sensitive and Decisive Patterns in Explainable AI: A Case Study of Model Interpretation in Geometric Deep Learning Jiajun Zhu Siqi Miao Rex Ying Pan Li 38 1 0 30 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin Jacob Helwig Shurui Gui Shuiwang Ji 39 7 0 11 Jun 2024
Equivariant Neural Tangent Kernels Philipp Misof Pan Kessel Jan E. Gerken 55 0 0 10 Jun 2024
Neural Isometries: Taming Transformations for Equivariant ML Thomas W. Mitchel Michael Taylor Vincent Sitzmann 28 0 0 29 May 2024
RiEMann: Near Real-Time SE(3)-Equivariant Robot Manipulation without Point Cloud Segmentation Chongkai Gao Zhengrong Xue Shuying Deng Tianhai Liang Siqi Yang Lin Shao Huazhe Xu 3DPC 36 10 0 28 Mar 2024
G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups Sourya Basu Suhas Lohit Matthew Brand 36 0 0 23 Feb 2024
Clifford-Steerable Convolutional Neural Networks Maksim Zhdanov David Ruhe Maurice Weiler Ana Lucic Johannes Brandstetter Patrick Forré 47 12 0 22 Feb 2024
Weisfeiler Leman for Euclidean Equivariant Machine Learning Snir Hordan Tal Amir Nadav Dym 44 5 0 04 Feb 2024
$Learning Polynomial Problems with $SL(2,\mathbb{R})$ Equivariance$ Learning Polynomial Problems with $SL(2,\mathbb{R})$ Equivariance Hannah Lawrence Mitchell Tong Harris 24 1 0 04 Dec 2023
$$\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 22 5 0 30 Nov 2023
Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation Ryan Liu A. Gandrakota J. Ngadiuba M. Spiropulu J. Vlimant 21 2 0 23 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 31 4 0 06 Nov 2023
19 Parameters Is All You Need: Tiny Neural Networks for Particle Physics A. Bogatskiy Timothy Hoffman Jan T. Offermann 20 3 0 24 Oct 2023
Lie Group Decompositions for Equivariant Neural Networks Mircea Mironenco Patrick Forré AI4CE 23 7 0 17 Oct 2023
Approximately Equivariant Quantum Neural Network for $p4m$ Group Symmetries in Images Su Yeon Chang Michele Grossi B. L. Saux S. Vallecorsa 49 13 0 03 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 29 3 0 12 Sep 2023
Neural Discovery of Permutation Subgroups Pavan Karjol Rohan Kashyap A. Prathosh 28 3 0 11 Sep 2023
A Unified Framework for Discovering Discrete Symmetries Pavan Karjol Rohan Kashyap Aditya Gopalan Prathosh A.P. 19 2 0 06 Sep 2023
Exploiting Code Symmetries for Learning Program Semantics Kexin Pei Weichen Li Qirui Jin Shuyang Liu Scott Geng Lorenzo Cavallaro Junfeng Yang Suman Jana 33 4 0 07 Aug 2023
Explainable Equivariant Neural Networks for Particle Physics: PELICAN A. Bogatskiy Timothy Hoffman David W. Miller Jan T. Offermann Xiaoyang Liu 29 24 0 31 Jul 2023
Non-parametric Hypothesis Tests for Distributional Group Symmetry Ke-Li Chiu Benjamin Bloem-Reddy 14 7 0 28 Jul 2023
Polynomial Width is Sufficient for Set Representation with High-dimensional Features Peihao Wang Shenghao Yang Shu Li Zhangyang Wang Pan Li 19 3 0 08 Jul 2023
Any-dimensional equivariant neural networks Eitan Levin Mateo Díaz 21 6 0 10 Jun 2023
A General Framework for Equivariant Neural Networks on Reductive Lie Groups Ilyes Batatia Mario Geiger José M. Muñoz Tess E. Smidt L. Silberman Christoph Ortner AI4CE 27 11 0 31 May 2023
Spontaneous Symmetry Breaking in Generative Diffusion Models G. Raya L. Ambrogioni DiffM 17 30 0 31 May 2023
Clifford Group Equivariant Neural Networks David Ruhe Johannes Brandstetter Patrick Forré 26 35 0 18 May 2023
iPINNs: Incremental learning for Physics-informed neural networks Aleksandr Dekhovich M. Sluiter David Tax Miguel A. Bessa AI4CE DiffM 12 10 0 10 Apr 2023
Computing equivariant matrices on homogeneous spaces for Geometric Deep Learning and Automorphic Lie Algebras V. Knibbeler 30 1 0 13 Mar 2023
A General Theory of Correct, Incorrect, and Extrinsic Equivariance Dian Wang Xu Zhu Jung Yeon Park Mingxi Jia Guanang Su Robert W. Platt Robin G. Walters 26 13 0 08 Mar 2023
Oracle-Preserving Latent Flows Alexander Roman Roy T. Forestano Konstantin T. Matchev Katia Matcheva Eyup B. Unlu DRL 24 5 0 02 Feb 2023
Deep Learning Symmetries and Their Lie Groups, Algebras, and Subalgebras from First Principles Roy T. Forestano Konstantin T. Matchev Katia Matcheva Alexander Roman Eyup B. Unlu Sarunas Verner AI4CE 28 21 0 13 Jan 2023
Brauer's Group Equivariant Neural Networks Edward Pearce-Crump AI4CE 13 15 0 16 Dec 2022
Lorentz group equivariant autoencoders Zichun Hao Raghav Kansal Javier Mauricio Duarte N. Chernyavskaya BDL DRL AI4CE 23 23 0 14 Dec 2022
Feature Selection with Distance Correlation Ranit Das Gregor Kasieczka David Shih 21 14 0 30 Nov 2022
Invariance-Aware Randomized Smoothing Certificates Jan Schuchardt Stephan Günnemann AAML 26 5 0 25 Nov 2022