Improving new physics searches with diffusion models for event observables and jet constituents

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2020

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G. Kasieczka et al., The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics , Rept. Prog. Phys. 84

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2021

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J. Batson, C.G. Haaf, Y. Kahn and D.A. Roberts, Topological Obstructions to Autoencoding , JHEP 04

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2021

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J.H. Collins, P. Martín-Ramiro, B. Nachman and D. Shih, Comparing weak- and unsupervised methods for resonant anomaly detection , Eur. Phys. J. C 81

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2021

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D. Shih, M.R. Buckley, L. Necib and J. Tamanas, via machinae: Searching for stellar streams using unsupervised machine learning , Mon. Not. Roy. Astron. Soc. 509

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2021

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B.M. Dillon, R. Mastandrea and B. Nachman, Self-supervised anomaly detection for new physics , Phys. Rev. D 106

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2022

Later among the works it cites.

M. Birman, B. Nachman, R. Sebbah, G. Sela, O. Turetz and S. Bressler, Data-directed search for new physics based on symmetries of the SM , Eur. Phys. J. C 82

Original

2022

Later among the works it cites.

M. Letizia, G. Losapio, M. Rando, G. Grosso, A. Wulzer, M. Pierini et al., Learning new physics efficiently with nonparametric methods , Eur. Phys. J. C 82

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2022

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C. Fanelli, J. Giroux and Z. Papandreou, ‘Flux+Mutability’: a conditional generative approach to one-class classification and anomaly detection , Mach. Learn. Sci. Tech. 3

Original

2022

Later among the works it cites.

T. Finke, M. Krämer, M. Lipp and A. Mück, Boosting mono-jet searches with model-agnostic machine learning , JHEP 08

Original

2022

Later among the works it cites.

R. Verheyen, Event Generation and Density Estimation with Surjective Normalizing Flows , SciPost Phys. 13

Original

2022

Later among the works it cites.

V. Mikuni and B. Nachman, Score-based generative models for calorimeter shower simulation , Phys. Rev. D 106

2022

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S. Bieringer, A. Butter, S. Diefenbacher, E. Eren, F. Gaede, D. Hundhausen et al., Calomplification — the power of generative calorimeter models , JINST 17

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2022

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ATLAS Collaboration, SUSY Summary Plots June 2021 , Jun, 2021 · 2023

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ATLAS Collaboration, Summary Plots from ATLAS Searches for Pair-Produced Leptoquarks , Jun, 2021 · 2023

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CMS Collaboration, CMS EXO sumary plots at 13TeV , 2022 · 2023

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CMS Collaboration, CMS B2G physics results summary , 2022 · 2023

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J.A. Raine, S. Klein, D. Sengupta and T. Golling, CURTAINs for your sliding window: Constructing unobserved regions by transforming adjacent intervals , Front. Big Data 6

Original

2023

Closest in time.

T. Golling, S. Klein, R. Mastandrea and B. Nachman, Flow-enhanced transportation for anomaly detection , Phys. Rev. D 107

Original

2023

Closest in time.

T. Dorigo, M. Fumanelli, C. Maccani, M. Mojsovska, G.C. Strong and B. Scarpa, RanBox: anomaly detection in the copula space , JHEP 01

Original

2023

Closest in time.

T. Buss, B.M. Dillon, T. Finke, M. Krämer, A. Morandini, A. Mück et al., What’s anomalous in LHC jets? , SciPost Phys. 15

Original

2023

Closest in time.

S. Alvi, C.W. Bauer and B. Nachman, Quantum anomaly detection for collider physics , JHEP 02

Original

2023

Closest in time.

S. Caron, R.R. de Austri and Z. Zhang, Mixture-of-Theories training: can we find new physics and anomalies better by mixing physical theories? , JHEP 03

Original

2023

Closest in time.

S.E. Park, P. Harris and B. Ostdiek, Neural embedding: learning the embedding of the manifold of physics data , JHEP 07

Original

2023

Closest in time.

J.F. Kamenik and M. Szewc, Null hypothesis test for anomaly detection , Phys. Lett. B 840

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2023

Closest in time.

G. Kasieczka, R. Mastandrea, V. Mikuni, B. Nachman, M. Pettee and D. Shih, Anomaly detection under coordinate transformations , Phys. Rev. D 107

Original

2023

Closest in time.

J. Schuhmacher, L. Boggia, V. Belis, E. Puljak, M. Grossi, M. Pierini et al., Unravelling physics beyond the standard model with classical and quantum anomaly detection , Mach. Learn. Sci. Tech. 4

Original

2023

Closest in time.

L. Vaslin, V. Barra and J. Donini, GAN-AE: an anomaly detection algorithm for New Physics search in LHC data , Eur. Phys. J. C 83

Original

2023

Closest in time.