Fetching the paper…
Reading the bibliography…
Classification of jets with deep learning has gained significant attention in recent times.
1901
Earlier work this paper cites.
H. Qu and L. Gouskos, ParticleNet: Jet Tagging via Particle Clouds , 1902.08570
1902
Earlier work this paper cites.
1902
Earlier work this paper cites.
1902
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.
1921
Earlier work this paper cites.
Morgan-Kaufmann, 1992
A. Krogh and J. A. Hertz, A simple weight decay can improve generalization , in Advances in Neural Information Processing Systems 4 (J. E. Moody, S. J. Hanson and R. P. Lippmann, eds.), pp. 950–957 · 1992
Earlier work this paper cites.
F. V. Tkachov, Measuring multi - jet structure of hadronic energy flow or What is a jet? , Int. J. Mod. Phys. A12
1997
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. B641
2006
Earlier work this paper cites.
2008
Earlier work this paper cites.
J. Thaler and L.-T. Wang, Strategies to Identify Boosted Tops , JHEP 07
2008
Earlier work this paper cites.
2008
Earlier work this paper cites.
M. Bahr et al., Herwig++ Physics and Manual , Eur. Phys. J. C58
2008
Earlier work this paper cites.
M. Cacciari, G. P. Salam and G. Soyez, The Anti-k(t) jet clustering algorithm , JHEP 04
2008
Earlier work this paper cites.
2009
Earlier work this paper cites.
T. Plehn, G. P. Salam and M. Spannowsky, Fat Jets for a Light Higgs , Phys. Rev. Lett. 104
2010
Earlier work this paper cites.
T. Plehn, M. Spannowsky, M. Takeuchi and D. Zerwas, Stop Reconstruction with Tagged Tops , JHEP 10
2010
Earlier work this paper cites.
J. Gallicchio and M. D. Schwartz, Seeing in Color: Jet Superstructure , Phys. Rev. Lett. 105
2010
Earlier work this paper cites.
D. Krohn, J. Thaler and L.-T. Wang, Jet Trimming , JHEP 02
2010
Earlier work this paper cites.
2010
Earlier work this paper cites.
X. Glorot and Y. Bengio, Understanding the difficulty of training deep feedforward neural networks , in Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (Y. W. Teh and M. Titterington, eds.), vol. 9 of Proceedings of Machine Learning Research , (Chia Laguna Resort, Sardinia, Italy), pp. 249–256, PMLR, 13–15 May, 2010
2010
Earlier work this paper cites.
D. E. Soper and M. Spannowsky, Finding physics signals with shower deconstruction , Phys. Rev. D84
2011
Earlier work this paper cites.
J. Thaler and K. Van Tilburg, Identifying Boosted Objects with N-subjettiness , JHEP 03
2011
Earlier work this paper cites.
J. Gallicchio and M. D. Schwartz, Quark and Gluon Tagging at the LHC , Phys. Rev. Lett. 107
2011
Earlier work this paper cites.
B. R. Webber, QCD Jets and Parton Showers , in Quantum chromodynamics and beyond: Gribov-80 memorial volume. Proceedings, Memorial Workshop devoted to the 80th birthday of V.N. Gribov, Trieste, Italy, May 26-28, 2010 , pp. 82–92, 2011 · 2011
Earlier work this paper cites.
M. Cacciari, G. P. Salam and G. Soyez, FastJet User Manual , Eur. Phys. J. C72
2012
Earlier work this paper cites.
S. Gieseke, C. Rohr and A. Siodmok, Colour reconnections in Herwig++ , Eur. Phys. J. C72
2012
Earlier work this paper cites.
D. E. Soper and M. Spannowsky, Finding top quarks with shower deconstruction , Phys. Rev. D87
2013
Cited alongside, same era.
2013
Cited alongside, same era.
2013
Cited alongside, same era.
R. D. Ball et al., Parton distributions with LHC data , Nucl. Phys. B867
2013
Cited alongside, same era.
D. E. Soper and M. Spannowsky, Finding physics signals with event deconstruction , Phys. Rev. D89
M. Tulio Ribeiro, S. Singh and C. Guestrin, Model-Agnostic Interpretability of Machine Learning , in 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016) , 2016 · 2016
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2014
Cited alongside, same era.
A. J. Larkoski, S. Marzani, G. Soyez and J. Thaler, Soft Drop , JHEP 05
2014
Cited alongside, same era.
Y.-T. Chien, Telescoping jets: Probing hadronic event structure with multiple R ’s , Phys. Rev. D90
2014
Cited alongside, same era.
A. J. Larkoski, I. Moult and D. Neill, Power Counting to Better Jet Observables , JHEP 12
2014
Cited alongside, same era.
2014
Cited alongside, same era.
P. Skands, S. Carrazza and J. Rojo, Tuning PYTHIA 8.1: the Monash 2013 Tune , Eur. Phys. J. C74
2014
Cited alongside, same era.
2015
Cited alongside, same era.
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
2018
Later among the works it cites.
T. Cheng, Recursive Neural Networks in Quark/Gluon Tagging , Comput. Softw. Big Sci. 2
2018
Later among the works it cites.
2018
Later among the works it cites.
F. A. Dreyer, G. P. Salam and G. Soyez, The Lund Jet Plane , JHEP 12
2018
Later among the works it cites.
2018
Later among the works it cites.
T. Cohen, M. Freytsis and B. Ostdiek, (Machine) Learning to Do More with Less , JHEP 02
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.
D. Alvarez Melis and T. Jaakkola, Towards robust interpretability with self-explaining neural networks , in Advances in Neural Information Processing Systems 31 (S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. Cesa-Bianchi and R. Garnett, eds.), pp. 7786–7795 · 2018
Later among the works it cites.
2019
Closest in time.
2019
Closest in time.
T. Heimel, G. Kasieczka, T. Plehn and J. M. Thompson, QCD or What? , SciPost Phys. 6
2019
Closest in time.