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A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning.
1902
Earlier work this paper cites.
A. Butter et al., The Machine Learning Landscape of Top Taggers , SciPost Phys. 7
1902
Earlier work this paper cites.
1903
Earlier work this paper cites.
T. S. Roy and A. H. Vijay, A robust anomaly finder based on autoencoder , 1903.02032
1903
Earlier work this paper cites.
1904
Earlier work this paper cites.
S. Amrouche et al., The Tracking Machine Learning challenge : Accuracy phase , 1904.06778
1904
Earlier work this paper cites.
1905
Earlier work this paper cites.
1905
Earlier work this paper cites.
C. Durkan, A. Bekasov, I. Murray and G. Papamakarios, Neural spline flows , 1906.04032
1906
Earlier work this paper cites.
1906
Earlier work this paper cites.
1907
Earlier work this paper cites.
1907
Earlier work this paper cites.
A. Butter, T. Plehn and R. Winterhalder, How to GAN LHC Events , SciPost Phys. 7
1907
Earlier work this paper cites.
1908
Earlier work this paper cites.
1909
Earlier work this paper cites.
B. Nachman and C. Shimmin, AI Safety for High Energy Physics , 1910.08606
1910
Earlier work this paper cites.
1911
Earlier work this paper cites.
1912
Earlier work this paper cites.
A. Alves and F. F. Freitas, Towards recognizing the light facet of the Higgs Boson , 1912.12532
1912
Earlier work this paper cites.
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever and R. Salakhutdinov, Dropout: A simple way to prevent neural networks from overfitting , Journal of Machine Learning Research 15
1958
Earlier work this paper cites.
J. Button, G. R. Kalbfleisch, G. R. Lynch, B. C. Maglić, A. H. Rosenfeld and M. L. Stevenson, Pion-Pion Interaction in the Reaction p ¯ + p → 2 π + + 2 π − + n π 0 \bar{p}+p\to 2\pi^{+}+2\pi^{-}+n\pi^{0} , Phys. Rev. 126
1962
Earlier work this paper cites.
H. G. Barrow, J. M. Tenenbaum, R. C. Bolles and H. C. Wolf, Parametric correspondence and Chamfer matching: Two new techniques for image matching , in Proceedings of the 5th International Joint Conference on Artificial Intelligence (KJCAI) , vol. 2, (San Francisco, CA, USA), p. 659, Morgan Kaufmann Publishers Inc., 1977, https://www.ijcai.org/Proceedings/77-2/Papers/024.pdf
1977
Earlier work this paper cites.
J. A. Hartigan and M. A. Wong, Algorithm as 136: A k-means clustering algorithm , Journal of the Royal Statistical Society. Series C (Applied Statistics) 28
1979
Earlier work this paper cites.
B. Nachman and D. Shih, Anomaly Detection with Density Estimation , Phys. Rev. D 101
2001
Earlier work this paper cites.
G. Kasieczka and D. Shih, DisCo Fever: Robust Networks Through Distance Correlation , 2001.05310
2001
Earlier work this paper cites.
2001
Earlier work this paper cites.
2001
Earlier work this paper cites.
2002
Earlier work this paper cites.
2003
Earlier work this paper cites.
K. S. Cranmer, “Searching for new physics: Contributions to LEP and the LHC.” http://weblib.cern.ch/abstract?CERN-THESIS-2005-011 , 2005
2005
Earlier work this paper cites.
“1st LHC Olympics Workshop, CERN.” https://indico.cern.ch/event/370125/ , 2005
2005
Earlier work this paper cites.
2005
Earlier work this paper cites.
2005
Earlier work this paper cites.
2005
Earlier work this paper cites.
“2nd LHC Olympics Workshop, CERN.” https://indico.cern.ch/event/370132/ , 2006
2006
Earlier work this paper cites.
“3rd LHC Olympics Workshop, KITP.” https://www.kitp.ucsb.edu/activities/lhco-c06 , 2006
2006
Earlier work this paper cites.
M. Cacciari and G. P. Salam, Dispelling the N 3 N^{3} myth for the k t k_{t} jet-finder , Phys. Lett. B 641
2006
Earlier work this paper cites.
T. Sjöstrand, S. Mrenna and P. Z. Skands, PYTHIA 6.4 Physics and Manual , JHEP 05
2006
Earlier work this paper cites.
“4th LHC Olympics Workshop, Princeton.” http://physics.princeton.edu/lhc-workshop/LHCO4/ , 2007
2007
Earlier work this paper cites.
F. Pérez and B. E. Granger, IPython: a system for interactive scientific computing , Computing in Science and Engineering 9
2007
Earlier work this paper cites.
2007
Earlier work this paper cites.
J. Shlomi, P. Battaglia and J.-R. Vlimant, Graph Neural Networks in Particle Physics , 2007.13681
2007
Earlier work this paper cites.
C. K. Khosa and V. Sanz, Anomaly Awareness , 2007.14462
2007
Earlier work this paper cites.
2007
Earlier work this paper cites.
M. Cacciari, G. P. Salam and G. Soyez, The anti- k t k_{t} jet clustering algorithm , JHEP 04
2008
Earlier work this paper cites.
M. Bahr et al., Herwig++ Physics and Manual , Eur. Phys. J. C 58
2008
Earlier work this paper cites.
2009
Cited alongside, same era.
2010
Cited alongside, same era.
W. McKinney, Data structures for statistical computing in python , in Proceedings of the 9th Python in Science Conference (S. van der Walt and J. Millman, eds.), pp. 51 – 56, 2010
2010
Cited alongside, same era.
V. Mikuni and F. Canelli, Unsupervised clustering for collider physics , 2010.07106
2010
Cited alongside, same era.
CMS Collaboration, “Model Unspecific Search for New Physics in p p pp Collisions at s = \sqrt{s}= 7 TeV.” http://cds.cern.ch/record/1360173 , 2011
2017
Later among the works it cites.
2017
Later among the works it cites.
K. Datta and A. Larkoski, How Much Information is in a Jet? , JHEP 06
2017
Later among the works it cites.
G. Papamakarios, T. Pavlakou and I. Murray, Masked autoregressive flow for density estimation , 2017
2017
Later among the works it cites.
I. Higgins, L. Matthey, A. Pal, C. Burgess, X. Glorot, M. Botvinick et al., beta-vae: Learning basic visual concepts with a constrained variational framework , in ICLR , 2017
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2011
Cited alongside, same era.
Springer, 2011
S. Koranne, Hierarchical data format 5: Hdf5 , in Handbook of Open Source Tools , pp. 191–200 · 2011
Cited alongside, same era.
L. Moneta, K. Belasco, K. Cranmer, S. Kreiss, A. Lazzaro, D. Piparo et al., The roostats project , 2011
2011
Cited alongside, same era.
J. Thaler and K. Van Tilburg, Identifying Boosted Objects with N-subjettiness , JHEP 03
2011
Cited alongside, same era.
2011
Cited alongside, same era.
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel et al., Scikit-learn: Machine learning in Python , Journal of Machine Learning Research 12
2011
Cited alongside, same era.
Cambridge University Press, 2, 2011
R. Ellis, W. Stirling and B. Webber, QCD and collider physics , vol. 8 · 2011
Cited alongside, same era.
2011
Cited alongside, same era.
2017
Later among the works it cites.
Z.-H. Zhou, A brief introduction to weakly supervised learning , National Science Review 5
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
K. Datta and A. J. Larkoski, Novel Jet Observables from Machine Learning , JHEP 03
2018
Later among the works it cites.
J. Duarte et al., Fast inference of deep neural networks in FPGAs for particle physics , JINST 13
2018
Later among the works it cites.
ATLAS Collaboration, “Exotic Physics Searches.” https://twiki.cern.ch/twiki/bin/view/AtlasPublic/ExoticsPublicResults , 2019
2019
Later among the works it cites.
ATLAS Collaboration, “Supersymmetry searches.” https://twiki.cern.ch/twiki/bin/view/AtlasPublic/SupersymmetryPublicResults , 2019
2019
Later among the works it cites.
ATLAS Collaboration, “Higgs and Diboson Searches.” https://twiki.cern.ch/twiki/bin/view/AtlasPublic/HDBSPublicResults , 2019
2019
Later among the works it cites.
CMS Collaboration, “CMS Exotica Public Physics Results.” https://twiki.cern.ch/twiki/bin/view/CMSPublic/PhysicsResultsEXO , 2019
2019
Later among the works it cites.
CMS Collaboration, “CMS Supersymmetry Physics Results.” https://twiki.cern.ch/twiki/bin/view/CMSPublic/PhysicsResultsSUS , 2019
2019
Later among the works it cites.
CMS Collaboration, “CMS Beyond-two-generations (B2G) Public Physics Results.” https://twiki.cern.ch/twiki/bin/view/CMSPublic/PhysicsResultsB2G , 2019
2019
Later among the works it cites.
LHCb Collaboration, “Publications of the QCD, Electroweak and Exotica Working Group.” http://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/Summary_QEE.html , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
G. Kasieczka, B. Nachman and D. Shih, “Official Datasets for LHC Olympics 2020 Anomaly Detection Challenge.” https://doi.org/10.5281/zenodo.3596919 , Nov., 2019
2019
Later among the works it cites.
Curran Associates, Inc., 2019
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan et al., Pytorch: An imperative style, high-performance deep learning library , in Advances in Neural Information Processing Systems 32 , pp. 8024–8035 · 2019
Later among the works it cites.
10.5281/zenodo.3832254
G. Kasieczka, B. Nachman and D. Shih, R&D Dataset for LHC Olympics 2020 Anomaly Detection Challenge , Apr., 2019 · 2019
Later among the works it cites.
10.5281/zenodo.3594321
N. Dawe, E. Rodrigues, H. Schreiner, S. Meehan, M. R., D. Kalinkin et al., scikit-hep/pyjet: 1.6.0 , Dec., 2019 · 2019
Later among the works it cites.
2019
Later among the works it cites.
T. Heimel, G. Kasieczka, T. Plehn and J. M. Thompson, QCD or What? , SciPost Phys. 6
2019
Later among the works it cites.
2019
Later among the works it cites.
R. T. D’Agnolo and A. Wulzer, Learning New Physics from a Machine , Phys. Rev. D 99
2019
Later among the works it cites.
D. Hendrycks, M. Mazeika, S. Kadavath and D. Song, Using self-supervised learning can improve model robustness and uncertainty , 2019
2019
Later among the works it cites.
D. Hendrycks, M. Mazeika and T. Dietterich, Deep anomaly detection with outlier exposure , 2019
2019
Later among the works it cites.
CMS Collaboration, “MUSiC, a model unspecific search for new physics, in p p pp collisions at s = 13 \sqrt{s}=13 TeV.” https://cds.cern.ch/record/2718811 , 5, 2020
2020
Later among the works it cites.
“LHC Olympics 2020.” https://lhco2020.github.io/homepage/ , 2020
2020
Later among the works it cites.
“Anomaly Detection Session, Machine Learning for Jets Workshop.” https://indico.cern.ch/event/809820/sessions/329216/#20200116 , 2020
2020
Later among the works it cites.
“Anomaly Detection Mini-Workshop.” https://indico.desy.de/indico/event/25341/ , 2020
2020
Later among the works it cites.
10.5281/zenodo.4289190
N. Dawe, E. Rodrigues, H. Schreiner, B. Ostdiek, D. Kalinkin, M. R. et al., scikit-hep/pyjet: Version 1.8.0 , Nov., 2020 · 2020
Later among the works it cites.
L. Vaslin, J. Donini and H. Schreiner, “pyBumpHunter.” https://github.com/lovaslin/pyBumpHunter , 2020
2020
Later among the works it cites.
2020
Later among the works it cites.
T. Chen, S. Kornblith, K. Swersky, M. Norouzi and G. Hinton, Big self-supervised models are strong semi-supervised learners , 2020
2020
Later among the works it cites.
Y. Ouali, C. Hudelot and M. Tami, An overview of deep semi-supervised learning , 2020
2020
Later among the works it cites.
L. Ruff, R. A. Vandermeulen, N. Görnitz, A. Binder, E. Müller, K.-R. Müller et al., Deep semi-supervised anomaly detection , 2020
2020
Later among the works it cites.
“Via Machinae: Anomaly Detection of Stellar Streams.” https://indico.desy.de/event/25341/contributions/56824/attachments/36785/46006/StreamFinding.pdf , 2020
2020
Later among the works it cites.
M. Feickert and B. Nachman, “A living review of machine learning for particle physics.” https://iml-wg.github.io/HEPML-LivingReview/ , 2020
2020
Later among the works it cites.