5 citations · 5 across the 3 of their papers we have counts for
4 papers
Machine Learning based KNO-scaling of charged hadron multiplicities with Hijing++
Gábor Bíró, Gergely Gábor Barnaföldi
The scaling properties of the final state charged hadron and mean jet multiplicity distributions, calculated by deep residual neural network architectures with different complexiti…
Dedicated Analysis Facility for HEP Experiments
Gábor Bíró, Gergely Gábor Barnaföldi, Péter Lévai
High-energy physics (HEP) provides ever-growing amount of data. To analyse these, continuously-evolving computational power is required in parallel by extending the storage capacit…
Testing of KNO-scaling of charged hadron multiplicities within a Machine Learning based approach
Gábor Bíró, Bence Tankó-Bartalis, Gergely Gábor Barnaföldi
The results of a Machine Learning-based method is presented here to investigate the scaling properties of the final state charged hadron and mean jet multiplicity distributions. De…
Machine learning methods for Schlieren imaging of a plasma channel in tenuous atomic vapor
Gábor Bíró, Mihály Pocsai, Imre Ferenc Barna +2
We investigate the usage of a Schlieren imaging setup to measure the geometrical dimensions of a plasma channel in atomic vapor. Near resonant probe light is used to image the plas…