Adversarially Learned Anomaly Detection on CMS Open Data: re-discovering the top quark
Not on the map. Why?
Abstract (arXiv)
We apply an Adversarially Learned Anomaly Detection (ALAD) algorithm to the problem of detecting new physics processes in proton-proton collisions at the Large Hadron Collider. Anomaly detection based on ALAD matches performances reached by Variational Autoencoders, with a substantial improvement in some cases. Training the ALAD algorithm on 4.4 fb-1 of 8 TeV CMS Open Data, we show how a data-driven anomaly detection and characterization would work in real life, re-discovering the top quark by identifying the main features of the t-tbar experimental signature at the LHC.
Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 May 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 8; 2022: 2; 2023: 3; 2024: 0; 2025: 4; 2026: 1.
18 papers.
Sort:
- 2021Machine Learning in the Search for New Fundamental Physicscited by 50
- 2021The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collidercited by 28
- 2023Quantum anomaly detection in the latent space of proton collision events at the LHCcited by 21
- 2021Better Latent Spaces for Better Autoencoderscited by 20
- 2021Bump Hunting in Latent Spacecited by 19
- 2023Deep Generative Models for Detector Signature Simulation: A Taxonomic Reviewcited by 18
- 2021Understanding Event-Generation Networks via Uncertaintiescited by 17
- 2021Challenges for Unsupervised Anomaly Detection in Particle Physicscited by 16
- 2021Online-compatible Unsupervised Non-resonant Anomaly Detectioncited by 15
- 2021Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detectioncited by 13
- 2022Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learningcited by 10
- 2023Unravelling physics beyond the standard model with classical and quantum anomaly detectioncited by 9
6 more
- 2022Machine-Learning Compression for Particle Physics Discoveriescited by 3
- 2025Enhancing anomaly detection with topology-aware autoencoderscited by 3
- 2026Model-Agnostic Signal Discovery with Machine Learning: Bridging the Gap Between Theory and Practicecited by 3
- 2025AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testingcited by 2
- 2025TRANSIT your events into a new mass: Fast background interpolation for weakly-supervised anomaly searchescited by 0
- 2025Strengthening Anomaly Awarenesscited by 0
- 2026Model-Agnostic Signal Discovery with Machine Learning: Bridging the Gap Between Theory and Practice29 May 2026
- 2025AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testing24 Oct 2025
- 2025Strengthening Anomaly Awareness15 Apr 2025
- 2025TRANSIT your events into a new mass: Fast background interpolation for weakly-supervised anomaly searches6 Mar 2025
- 2025Enhancing anomaly detection with topology-aware autoencoders14 Feb 2025
- 2023Deep Generative Models for Detector Signature Simulation: A Taxonomic Review15 Dec 2023
- 2023Unravelling physics beyond the standard model with classical and quantum anomaly detection25 Jan 2023
- 2023Quantum anomaly detection in the latent space of proton collision events at the LHC25 Jan 2023
- 2022Machine-Learning Compression for Particle Physics Discoveries20 Oct 2022
- 2022Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning15 Sep 2022
- 2021Machine Learning in the Search for New Fundamental Physics7 Dec 2021
- 2021Online-compatible Unsupervised Non-resonant Anomaly Detection11 Nov 2021
6 more
- 2021Challenges for Unsupervised Anomaly Detection in Particle Physics13 Oct 2021
- 2021The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider28 May 2021
- 2021Better Latent Spaces for Better Autoencoders16 Apr 2021
- 2021Understanding Event-Generation Networks via Uncertainties9 Apr 2021
- 2021Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detection5 Apr 2021
- 2021Bump Hunting in Latent Space11 Mar 2021
- 2021Machine Learning in the Search for New Fundamental Physicscited by 50
- 2021The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collidercited by 28
- 2023Quantum anomaly detection in the latent space of proton collision events at the LHCcited by 21
- 2021Better Latent Spaces for Better Autoencoderscited by 20
- 2021Bump Hunting in Latent Spacecited by 19
- 2023Deep Generative Models for Detector Signature Simulation: A Taxonomic Reviewcited by 18
- 2021Understanding Event-Generation Networks via Uncertaintiescited by 17
- 2021Challenges for Unsupervised Anomaly Detection in Particle Physicscited by 16
- 2021Online-compatible Unsupervised Non-resonant Anomaly Detectioncited by 15
- 2021Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detectioncited by 13
- 2022Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learningcited by 10
- 2023Unravelling physics beyond the standard model with classical and quantum anomaly detectioncited by 9
12 most cited of 18 All 18 (JSON)
- 2026Model-Agnostic Signal Discovery with Machine Learning: Bridging the Gap Between Theory and Practice29 May 2026
- 2025AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testing24 Oct 2025
- 2025Strengthening Anomaly Awareness15 Apr 2025
- 2025TRANSIT your events into a new mass: Fast background interpolation for weakly-supervised anomaly searches6 Mar 2025
- 2025Enhancing anomaly detection with topology-aware autoencoders14 Feb 2025
- 2023Deep Generative Models for Detector Signature Simulation: A Taxonomic Review15 Dec 2023
- 2023Unravelling physics beyond the standard model with classical and quantum anomaly detection25 Jan 2023
- 2023Quantum anomaly detection in the latent space of proton collision events at the LHC25 Jan 2023
- 2022Machine-Learning Compression for Particle Physics Discoveries20 Oct 2022
- 2022Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning15 Sep 2022
- 2021Machine Learning in the Search for New Fundamental Physics7 Dec 2021
- 2021Online-compatible Unsupervised Non-resonant Anomaly Detection11 Nov 2021
12 newest of 18 All 18 (JSON)