1.1k citations · 8.7k across the 150 of their papers we have counts for
3 papers · 1 filter
Robust Neural Particle Identification Models
Aziz Temirkhanov, Artem Ryzhikov, Denis Derkach +3
The volume of data processed by the Large Hadron Collider experiments demands sophisticated selection rules typically based on machine learning algorithms. One of the shortcomings…
Generative models uncertainty estimation
Lucio Anderlini, Constantine Chimpoesh, Nikita Kazeev +1
In recent years fully-parametric fast simulation methods based on generative models have been proposed for a variety of high-energy physics detectors. By their nature, the quality…
Towards Reliable Neural Generative Modeling of Detectors
Lucio Anderlini, Matteo Barbetti, Denis Derkach +3
The increasing luminosities of future data taking at Large Hadron Collider and next generation collider experiments require an unprecedented amount of simulated events to be produc…