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Model-agnostic anomaly detection is one of the promising approaches in the search for new beyond the standard model physics.
CMS High Level Trigger
Tejinder Virdee, Achille Petrilli, and Austin Ball · 2007
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The level-1 global trigger for the cms experiment at lhc
Manfred Jeitler, A Taurok, H Bergauer, C Deldicque, J Erö, M Ghete, P Glaser, K Kastner, I Mikulec, T Nöbauer, et al · 2007
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Identifying boosted objects with n-subjettiness
Jesse Thaler and Ken Van Tilburg · 2011
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Observation of a new boson at a mass of 125 gev with the cms experiment at the lhc
Serguei Chatrchyan, Vardan Khachatryan, Albert M Sirunyan, Armen Tumasyan, Wolfgang Adam, Ernest Aguilo, Thomas Bergauer, M Dragicevic, J Erö, C Fabjan, et al · 2012
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CMS Technical Design Report for the Level-1 Trigger Upgrade
A Tapper and Darin Acosta · 2013
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Effective approaches to attention-based neural machine translation, 2015
Minh-Thang Luong, Hieu Pham, and Christopher D. Manning · 2015
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A point set generation network for 3d object reconstruction from a single image, 2016
Haoqiang Fan, Hao Su, and Leonidas Guibas · 2016
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Deep sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Russ R Salakhutdinov, and Alexander J Smola · 2017
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beta-VAE: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2017
Earlier work this paper cites.
Fast inference of deep neural networks in FPGAs for particle physics
Javier Duarte et al · 2018
Cited alongside, same era.
Searching for new physics with deep autoencoders (2018)
M Farina, Y Nakai, and D Shih · 2018
Cited alongside, same era.
Qcd or what?
Theo Heimel, Gregor Kasieczka, Tilman Plehn, and Jennifer Thompson · 2019
Cited alongside, same era.
Anomaly detection with density estimation
Benjamin Nachman and David Shih · 2020
Cited alongside, same era.
Deep learning for anomaly detection: A review
Guansong Pang, Chunhua Shen, Longbing Cao, and Anton Van Den Hengel · 2021
Cited alongside, same era.
The lhc olympics 2020 a community challenge for anomaly detection in high energy physics
Gregor Kasieczka, Benjamin Nachman, David Shih, Oz Amram, Anders Andreassen, Kees Benkendorfer, Blaz Bortolato, Gustaaf Brooijmans, Florencia Canelli, Jack H Collins, et al · 2021
Going deeper with image transformers, 2021
Hugo Touvron, Matthieu Cord, Alexandre Sablayrolles, Gabriel Synnaeve, and Hervé Jégou · 2021
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Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 mhz at the large hadron collider
Ekaterina Govorkova, Ema Puljak, Thea Aarrestad, Thomas James, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Nicolò Ghielmetti, Maksymilian Graczyk, Sioni Summers, et al · 2022
Later among the works it cites.
Deep set auto encoders for anomaly detection in particle physics
Bryan Ostdiek · 2022
Later among the works it cites.
Permutation equivariant layers for higher order interactions
Horace Pan and Risi Kondor · 2022
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Auto-encoding variational bayes, 2022
Diederik P Kingma and Max Welling · 2022
Later among the works it cites.
Particle transformer for jet tagging, 2022
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Cited alongside, same era.
Anomaly detection with convolutional graph neural networks
Oliver Atkinson, Akanksha Bhardwaj, Christoph Englert, Vishal S Ngairangbam, and Michael Spannowsky · 2021
Cited alongside, same era.
Autoencoders for unsupervised anomaly detection in high energy physics
Thorben Finke, Michael Krämer, Alessandro Morandini, Alexander Mück, and Ivan Oleksiyuk · 2021
Cited alongside, same era.
Huilin Qu, Congqiao Li, and Sitian Qian · 2022
Later among the works it cites.
Lorentz group equivariant autoencoders
Zichun Hao, Raghav Kansal, Javier Duarte, and Nadezda Chernyavskaya · 2023
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Attention is all you need, 2023
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2023
Closest in time.