<p>Presentation at the 23rd International Conference on Computing in High-Energy and Nuclear Physics (<a href="http://chep2018.org">CHEP2018</a>) on 10 July 2018 (<a href="https://indico.cern.ch/event/587955/contributions/2937504/">https://indico.cern.ch/event/587955/contributions/2937504/</a>).</p
Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments ove...
On behalf of the ATLAS Collaboration - Proceedings of the 37 International Conference on High Energy...
Deep learning neural network technique is one of the most efficient and general approach of multivar...
<p>Presentation at the 23rd International Conference on Computing in High-Energy and Nuclear Physics...
I discuss the choice of evaluation metrics for binary classifiers in High Energy Physics (HEP) event...
Presentation at the 13th Quark Confinement and the Hadron Spectrum conference on 03 August 2018 (htt...
Presentation at the 24th International Conference on Computing in High-Energy and Nuclear Physics (C...
HEP event selection is traditionally considered a binary classification problem, involving the dicho...
The field of high energy physics aims to discover the underlying structure of matter by searching fo...
Datasets in modern High Energy Physics (HEP) experiments are often described by dozens or even hundr...
An algorithm for optimization of signal significance or any other classification figure of merit (FO...
Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments ove...
Datasets in modern High Energy Physics (HEP) experiments are often described by dozens or even hundr...
Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments ove...
Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments ove...
Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments ove...
On behalf of the ATLAS Collaboration - Proceedings of the 37 International Conference on High Energy...
Deep learning neural network technique is one of the most efficient and general approach of multivar...
<p>Presentation at the 23rd International Conference on Computing in High-Energy and Nuclear Physics...
I discuss the choice of evaluation metrics for binary classifiers in High Energy Physics (HEP) event...
Presentation at the 13th Quark Confinement and the Hadron Spectrum conference on 03 August 2018 (htt...
Presentation at the 24th International Conference on Computing in High-Energy and Nuclear Physics (C...
HEP event selection is traditionally considered a binary classification problem, involving the dicho...
The field of high energy physics aims to discover the underlying structure of matter by searching fo...
Datasets in modern High Energy Physics (HEP) experiments are often described by dozens or even hundr...
An algorithm for optimization of signal significance or any other classification figure of merit (FO...
Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments ove...
Datasets in modern High Energy Physics (HEP) experiments are often described by dozens or even hundr...
Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments ove...
Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments ove...
Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments ove...
On behalf of the ATLAS Collaboration - Proceedings of the 37 International Conference on High Energy...
Deep learning neural network technique is one of the most efficient and general approach of multivar...
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