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The Matrix Element Method (MEM) is a powerful method to extract information from measured events at collider experiments.
1901
Earlier work this paper cites.
1911
Earlier work this paper cites.
S. Nitish, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Dropout: A simple way to prevent neural networks from overfitting,” Journal of Machine Learning Research
1958
Earlier work this paper cites.
G. P. Lepage, “A new algorithm for adaptive multidimensional integration,” Journal of Computational Physics
1978
Earlier work this paper cites.
R. Dalitz and G. R. Goldstein, “Test of analysis method for top-antitop production and decay events,” Proc. Roy. Soc. Lond. A
1999
Earlier work this paper cites.
2001
Earlier work this paper cites.
2001
Earlier work this paper cites.
2009
Earlier work this paper cites.
2011
Earlier work this paper cites.
M. Kuusela, T. Vatanen, E. Malmi, T. Raiko, T. Aaltonen, and Y. Nagai, “Semi-supervised anomaly detection - towards model-independent searches of new physics,” in Journal of Physics Conference Series · 2012
Earlier work this paper cites.
2012
Earlier work this paper cites.
C. Cortes, M. Mohri, and A. Rostamizadeh, “L2 regularization for learning kernels,” CoRR
2012
Earlier work this paper cites.
2014
Earlier work this paper cites.
D. P. Kingma and J. Ba, “Adam: A Method for Stochastic Optimization,” arXiv e-prints
2014
Cited alongside, same era.
2015
Cited alongside, same era.
2015
Cited alongside, same era.
D. Schouten, A. DeAbreu, and B. Stelzer, “Accelerated matrix element method with parallel computing,” Computer Physics Communications
2015
Cited alongside, same era.
2017
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2018
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2018
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2018
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2015
Cited alongside, same era.
2015
Cited alongside, same era.
F. Chollet et al
2015
Cited alongside, same era.
http://tensorflow.org/ . Software available from tensorflow.org
M. A. et al, “TensorFlow: Large-scale machine learning on heterogeneous systems,” 2015 · 2015
Cited alongside, same era.
G. Louppe, M. Kagan, and K. Cranmer, “Learning to Pivot with Adversarial Networks,” arXiv e-prints
2016
Cited alongside, same era.
2016
Cited alongside, same era.
2016
Cited alongside, same era.
2016
Cited alongside, same era.
2018
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2018
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2018
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2018
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A. F. Agarap, “Deep learning using rectified linear units (relu),” CoRR
2018
Later among the works it cites.
2018
Later among the works it cites.
2019
Later among the works it cites.
2019
Later among the works it cites.
G. Grasseau, F. Beaudette, C. Perez, A. Zabi, A. Chiron, T. Strebler, and G. Hautreux, “Deployment of a matrix element method code for the tth channel analysis on gpu’s platform,” EPJ Web of Conferences
2019
Later among the works it cites.