Flow-enhanced transportation for anomaly detection

Golling, Tobias; Klein, Samuel; Mastandrea, Radha; Nachman, Benjamin

doi:10.1103/PhysRevD.107.096025

Title: Flow-enhanced transportation for anomaly detection

Journal Article · 30 May 2023 · Physical Review. D.

DOI: https://doi.org/10.1103/PhysRevD.107.096025 · OSTI ID:1975899

;

Not Available

View Journal Article

Cite

Export

Save

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: National Science Foundation (NSF); USDOE; USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1975899

Journal Information:: Physical Review. D., Journal Name: Physical Review. D. Journal Issue: 9 Vol. 107; ISSN PRVDAQ; ISSN 2470-0010

Publisher:: American Physical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

References (18)

A Family of Nonparametric Density Estimation Algorithms Tabak, E. G.; Turner, Cristina V. Communications on Pure and Applied Mathematics, Vol. 66, Issue 2 https://doi.org/10.1002/cpa.21423	journal	September 2012
Tag N’ Train: a technique to train improved classifiers on unlabeled data Amram, Oz; Suarez, Cristina Mantilla Journal of High Energy Physics, Vol. 2021, Issue 1 https://doi.org/10.1007/JHEP01(2021)153	journal	January 2021
DELPHES 3: a modular framework for fast simulation of a generic collider experiment de Favereau, J.; Delaere, C.; Demin, P. Journal of High Energy Physics, Vol. 2014, Issue 2 https://doi.org/10.1007/JHEP02(2014)057	journal	February 2014
Classification without labels: learning from mixed samples in high energy physics Metodiev, Eric M.; Nachman, Benjamin; Thaler, Jesse Journal of High Energy Physics, Vol. 2017, Issue 10 https://doi.org/10.1007/JHEP10(2017)174	journal	October 2017
An introduction to PYTHIA 8.2 Sjöstrand, Torbjörn; Ask, Stefan; Christiansen, Jesper R. Computer Physics Communications, Vol. 191 https://doi.org/10.1016/j.cpc.2015.01.024	journal	June 2015
Machine learning in the search for new fundamental physics Karagiorgi, Georgia; Kasieczka, Gregor; Kravitz, Scott Nature Reviews Physics, Vol. 4, Issue 6 https://doi.org/10.1038/s42254-022-00455-1	journal	May 2022
PYTHIA 6.4 physics and manual Sjöstrand, Torbjörn; Mrenna, Stephen; Skands, Peter Journal of High Energy Physics, Vol. 2006, Issue 05 https://doi.org/10.1088/1126-6708/2006/05/026	journal	May 2006
The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics Kasieczka, Gregor; Nachman, Benjamin; Shih, David Reports on Progress in Physics, Vol. 84, Issue 12 https://doi.org/10.1088/1361-6633/ac36b9	journal	December 2021
Anomaly detection with density estimation Nachman, Benjamin; Shih, David Physical Review D, Vol. 101, Issue 7 https://doi.org/10.1103/PhysRevD.101.075042	journal	April 2020
Simulation assisted likelihood-free anomaly detection Andreassen, Anders; Nachman, Benjamin; Shih, David Physical Review D, Vol. 101, Issue 9 https://doi.org/10.1103/PhysRevD.101.095004	journal	May 2020
Simulation-assisted decorrelation for resonant anomaly detection Benkendorfer, Kees; Le Pottier, Luc; Nachman, Benjamin Physical Review D, Vol. 104, Issue 3 https://doi.org/10.1103/PhysRevD.104.035003	journal	August 2021
Classifying anomalies through outer density estimation Hallin, Anna; Isaacson, Joshua; Kasieczka, Gregor Physical Review D, Vol. 106, Issue 5 https://doi.org/10.1103/PhysRevD.106.055006	journal	September 2022
Extending the search for new resonances with machine learning Collins, Jack H.; Howe, Kiel; Nachman, Benjamin Physical Review D, Vol. 99, Issue 1 https://doi.org/10.1103/PhysRevD.99.014038	journal	January 2019
Anomaly Detection for Resonant New Physics with Machine Learning Collins, Jack; Howe, Kiel; Nachman, Benjamin Physical Review Letters, Vol. 121, Issue 24 https://doi.org/10.1103/PhysRevLett.121.241803	journal	December 2018
Normalizing Flows: An Introduction and Review of Current Methods Kobyzev, Ivan; Prince, Simon; Brubaker, Marcus IEEE Transactions on Pattern Analysis and Machine Intelligence https://doi.org/10.1109/TPAMI.2020.2992934	journal	January 2020
Herwig++ physics and manual Bähr, Manuel; Gieseke, Stefan; Gigg, Martyn A. The European Physical Journal C, Vol. 58, Issue 4 https://doi.org/10.1140/epjc/s10052-008-0798-9	journal	November 2008
The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider Aarrestad, Thea; van Beekveld, Melissa; Bona, Marcella SciPost Physics, Vol. 12, Issue 1 https://doi.org/10.21468/SciPostPhys.12.1.043	journal	January 2022
CURTAINs for your sliding window: Constructing unobserved regions by transforming adjacent intervals Raine, John Andrew; Klein, Samuel; Sengupta, Debajyoti Frontiers in Big Data, Vol. 6 https://doi.org/10.3389/fdata.2023.899345	journal	March 2023

Similar Records

Enhancing IoT anomaly detection performance for federated learning

Journal Article · 2022 · Digital Communications and Networks · OSTI ID:1859795

Weinger, Brett; Kim, Jinoh; Sim, Alex; +3 more

Simulation-assisted decorrelation for resonant anomaly detection

Journal Article · 2021 · Physical Review. D. · OSTI ID:1812111

Benkendorfer, Kees; Le Pottier, Luc; Nachman, Benjamin

Self-supervised anomaly detection for new physics

Journal Article · 2022 · Physical Review D · OSTI ID:1886105

Dillon, Barry M.; Mastandrea, Radha; Nachman, Benjamin

Related Subjects

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Title: Flow-enhanced transportation for anomaly detection

Citation Formats

References (18)

Similar Records

Related Subjects