Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Germain, Cecile"'
Autor:
Amrouche, Sabrina, Basara, Laurent, Calafiura, Paolo, Emeliyanov, Dmitry, Estrade, Victor, Farrell, Steven, Germain, Cécile, Gligorov, Vladimir Vava, Golling, Tobias, Gorbunov, Sergey, Gray, Heather, Guyon, Isabelle, Hushchyn, Mikhail, Innocente, Vincenzo, Kiehn, Moritz, Kunze, Marcel, Moyse, Edward, Rousseau, David, Salzburger, Andreas, Ustyuzhanin, Andrey, Vlimant, Jean-Roch
This paper reports on the second "Throughput" phase of the Tracking Machine Learning (TrackML) challenge on the Codalab platform. As in the first "Accuracy" phase, the participants had to solve a difficult experimental problem linked to tracking accu
Externí odkaz:
http://arxiv.org/abs/2105.01160
Exploiting the rapid advances in probabilistic inference, in particular variational Bayes and variational autoencoders (VAEs), for anomaly detection (AD) tasks remains an open research question. Previous works argued that training VAE models only wit
Externí odkaz:
http://arxiv.org/abs/2010.05531
Autor:
Amrouche, Sabrina, Basara, Laurent, Calafiura, Paolo, Estrade, Victor, Farrell, Steven, Ferreira, Diogo R., Finnie, Liam, Finnie, Nicole, Germain, Cécile, Gligorov, Vladimir Vava, Golling, Tobias, Gorbunov, Sergey, Gray, Heather, Guyon, Isabelle, Hushchyn, Mikhail, Innocente, Vincenzo, Kiehn, Moritz, Moyse, Edward, Puget, Jean-Francois, Reina, Yuval, Rousseau, David, Salzburger, Andreas, Ustyuzhanin, Andrey, Vlimant, Jean-Roch, Wind, Johan Sokrates, Xylouris, Trian, Yilmaz, Yetkin
Publikováno v:
In: Escalera S., Herbrich R. (eds) The NeurIPS 2018 Competition. The Springer Series on Challenges in Machine Learning. Springer, Cham
This paper reports the results of an experiment in high energy physics: using the power of the "crowd" to solve difficult experimental problems linked to tracking accurately the trajectory of particles in the Large Hadron Collider (LHC). This experim
Externí odkaz:
http://arxiv.org/abs/1904.06778
Reliable data quality monitoring is a key asset in delivering collision data suitable for physics analysis in any modern large-scale High Energy Physics experiment. This paper focuses on the use of artificial neural networks for supervised and semi-s
Externí odkaz:
http://arxiv.org/abs/1808.00911
Publikováno v:
In Future Generation Computer Systems October 2013 29(8):2272-2283
Autor:
Rousseau, David, Calafiura, Paolo, Germain, Cecile, Innocente, Vincenzo, Cenci, Riccardo, Kagan, Michael, Guyon, Isabelle, Clark, David, Farrell, Steven, Carney, Rebecca, Salzburger, Andreas, Costanzo, Davide, Elsing, Markus, Golling, Tobias, Tong, Tony, Vlimant, Jean-Roch
Publikováno v:
International Conference on Computing in High Energy and Nuclear Physics
International Conference on Computing in High Energy and Nuclear Physics, Oct 2016, San Francisco, United States
International Conference on Computing in High Energy and Nuclear Physics, Oct 2016, San Francisco, United States
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9c68b2497075eada47e737a8e3ceb29b
https://hal.inria.fr/hal-01422939
https://hal.inria.fr/hal-01422939
Autor:
Adam-Bourdarios, Claire, Cowan, Glen, Germain, Cecile, Guyon, Isabelle, Kegl, B., Rousseau, David
Publikováno v:
International Conference on High Energy Physics(ICHEP) Conference
International Conference on High Energy Physics(ICHEP) Conference, Jul 2014, Valencia, Spain
International Conference on High Energy Physics(ICHEP) Conference, Jul 2014, Valencia, Spain
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::404b61c8cb7e3f7b900c57d8bf085811
https://inria.hal.science/hal-01111177
https://inria.hal.science/hal-01111177
Akademický článek
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Publikováno v:
2014 International Conference on Cloud & Autonomic Computing; 2014, p25-34, 10p
Autor:
DAWEI FENG, GERMAIN, CECILE
Publikováno v:
ACM Transactions on Autonomous & Adaptive Systems; Aug2015, Vol. 10 Issue 3, p20:1-20:25, 25p