Energy Flow Networks: Deep Sets for Particle Jets

11 October 2018

Papers citing "Energy Flow Networks: Deep Sets for Particle Jets"

50 / 70 papers shown

Title
Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning Sanghwan Bae Jiwoo Hong Min Young Lee Hanbyul Kim Jeongyeon Nam Donghyun Kwak OffRL LRM 53 3 0 04 Apr 2025
Learnable cut flow Jing Li Hao Sun OOD 46 0 0 28 Mar 2025
Lie-Equivariant Quantum Graph Neural Networks Jogi Suda Neto Roy T. Forestano S. Gleyzer K. Kong Konstantin T. Matchev Katia Matcheva 93 0 0 22 Nov 2024
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
Lorentz-Equivariant Quantum Graph Neural Network for High-Energy Physics Md Abrar Jahin Md. Akmol Masud Md Wahiduzzaman Suva M. Mridha Nilanjan Dey 48 1 0 03 Nov 2024
Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination Md Abrar Jahin Md. Akmol Masud M. Mridha Nilanjan Dey Zeyar Aung 54 0 0 03 Nov 2024
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 28 10 0 01 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
Particle Multi-Axis Transformer for Jet Tagging Muhammad Usman M. Shahid Maheen Ejaz Ummay Hani Nayab Fatima Abdul Rehman Khan Asifullah Khan Nasir Majid Mirza 33 3 0 09 Jun 2024
Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics Jonas Spinner Victor Bresó P. D. Haan Tilman Plehn Jesse Thaler Johann Brehmer AI4CE 29 16 0 23 May 2024
Moments of Clarity: Streamlining Latent Spaces in Machine Learning using Moment Pooling Rikab Gambhir Athis Osathapan Jesse Thaler 33 3 0 13 Mar 2024
OmniJet- $α$ : The first cross-task foundation model for particle physics Joschka Birk Anna Hallin Gregor Kasieczka AI4CE 35 22 0 08 Mar 2024
Jet Discrimination with Quantum Complete Graph Neural Network Yi-An Chen Kai-Feng Chen GNN 21 1 0 08 Mar 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 26 3 0 02 Feb 2024
Finetuning Foundation Models for Joint Analysis Optimization M. Vigl N. Hartman L. Heinrich 40 12 0 24 Jan 2024
Deep Generative Models for Detector Signature Simulation: A Taxonomic Review Baran Hashemi Claudius Krause 30 16 0 15 Dec 2023
Scaling Laws in Jet Classification Joshua D. Batson Yonatan Kahn 19 2 0 04 Dec 2023
A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks Roy T. Forestano Marçal Comajoan Cara Gopal Ramesh Dahale Zhongtian Dong S. Gleyzer ... Kyoungchul Kong Tom Magorsch Konstantin T. Matchev Katia Matcheva Eyup B. Unlu GNN 24 8 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 23 3 0 24 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
Graph Structure from Point Clouds: Geometric Attention is All You Need D. Murnane GNN 3DPC 8 4 0 31 Jul 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
Clifford Group Equivariant Neural Networks David Ruhe Johannes Brandstetter Patrick Forré 26 35 0 18 May 2023
Rethinking SO(3)-equivariance with Bilinear Tensor Networks C. Shimmin Zhelun Li Ema Smith 3DPC 20 0 0 20 Mar 2023
PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics Matthew Leigh Debasish Sengupta Guillaume Quétant J. A. Raine K. Zoch T. Golling DiffM 27 46 0 09 Mar 2023
EPiC-GAN: Equivariant Point Cloud Generation for Particle Jets E. Buhmann Gregor Kasieczka Jesse Thaler 3DPC 25 46 0 17 Jan 2023
Lorentz group equivariant autoencoders Zichun Hao Raghav Kansal Javier Mauricio Duarte N. Chernyavskaya BDL DRL AI4CE 26 23 0 14 Dec 2022
Feature Selection with Distance Correlation Ranit Das Gregor Kasieczka David Shih 24 14 0 30 Nov 2022
PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant Aggregator Network for Particle Physics A. Bogatskiy Timothy Hoffman David W. Miller Jan T. Offermann 16 30 0 01 Nov 2022
Machine-Learning Compression for Particle Physics Discoveries J. Collins Yifeng Huang S. Knapen Benjamin Nachman D. Whiteson 30 4 0 20 Oct 2022
A Detailed Study of Interpretability of Deep Neural Network based Top Taggers Ayush Khot Mark S. Neubauer Avik Roy AAML 33 16 0 09 Oct 2022
IRC-safe Graph Autoencoder for unsupervised anomaly detection Oliver Atkinson Akanksha Bhardwaj C. Englert P. Konar Vishal S. Ngairangbam M. Spannowsky 19 26 0 26 Apr 2022
Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges S. Thais P. Calafiura G. Chachamis G. Dezoort Javier Mauricio Duarte S. Ganguly Michael Kagan D. Murnane Mark S. Neubauer K. Terao PINN AI4CE 31 30 0 23 Mar 2022
Particle Transformer for Jet Tagging H. Qu Congqiao Li Sitian Qian ViT MedIm 24 97 0 08 Feb 2022
Domain-informed neural networks for interaction localization within astroparticle experiments Shixiao Liang A. Higuera C. Peters Venkat Roy W. Bajwa H. Shatkay C. Tunnell 17 7 0 15 Dec 2021
Machine Learning in the Search for New Fundamental Physics G. Karagiorgi Gregor Kasieczka S. Kravitz Benjamin Nachman David Shih AI4CE 42 113 0 07 Dec 2021
An Exploration of Learnt Representations of W Jets J. Collins DRL 26 12 0 22 Sep 2021
Particle Convolution for High Energy Physics C. Shimmin 17 15 0 05 Jul 2021
Shared Data and Algorithms for Deep Learning in Fundamental Physics L. Benato E. Buhmann M. Erdmann P. Fackeldey J. Glombitza ... T. Kuhr J. Steinheimer H. Stocker Tilman Plehn K. Zhou PINN OOD 24 15 0 01 Jul 2021
The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider T. Aarrestad M. Beekveld M. Bona A. Boveia S. Caron ... M. White E. Wulff E. Wallin K. Wozniak Z. Zhang 21 80 0 28 May 2021
Scaffolding Simulations with Deep Learning for High-dimensional Deconvolution Anders Andreassen Patrick T. Komiske E. Metodiev Benjamin Nachman Adithya Suresh Jesse Thaler UQCV 11 28 0 10 May 2021
End-to-End Jet Classification of Boosted Top Quarks with the CMS Open Data Michael Andrews Bjorn Burkle Yi-fan Chen Davide DiCroce S. Gleyzer ... N. Pervan Yusef Shafi Wei-Ju Sun Emanuele Usai Kun Yang 11 10 0 19 Apr 2021
Graph Generative Models for Fast Detector Simulations in High Energy Physics A. Hariri Darya Dyachkova Sergei Gleyzer AI4CE 24 6 0 05 Apr 2021
Topological Obstructions to Autoencoding Joshua D. Batson C. G. Haaf Yonatan Kahn Daniel A. Roberts AI4CE 34 37 0 16 Feb 2021
Point Cloud Transformers applied to Collider Physics Vinicius Mikuni F. Canelli ViT 14 55 0 09 Feb 2021
Sequence-based Machine Learning Models in Jet Physics Rafael Lima PINN 16 4 0 09 Feb 2021
A Living Review of Machine Learning for Particle Physics Matthew Feickert Benjamin Nachman KELM AI4CE 19 151 0 02 Feb 2021
MLPF: Efficient machine-learned particle-flow reconstruction using graph neural networks J. Pata Javier Mauricio Duarte J. Vlimant M. Pierini M. Spiropulu 107 76 0 21 Jan 2021