29 citations · 61 across the 6 of their papers we have counts for
4 papers · 1 filter
Deep Learning Applications to Particle Physics: from Monte Carlo simulation acceleration to ProtoDUNE reconstruction
Marco Rossi
The thesis arises in the context of deep learning applications to particle physics. The dissertation follows two main parallel streams: the development of hardware-accelerated tool…
Deep Learning strategies for ProtoDUNE raw data denoising
Marco Rossi, Sofia Vallecorsa
In this work, we investigate different machine learning-based strategies for denoising raw simulation data from the ProtoDUNE experiment. The ProtoDUNE detector is hosted by CERN a…
PDFFlow: hardware accelerating parton density access
Marco Rossi, Stefano Carrazza, Juan M. Cruz-Martinez
We present PDFFlow, a new software for fast evaluation of parton distribution functions (PDFs) designed for platforms with hardware accelerators. PDFs are essential for the calcula…
PDFFlow: parton distribution functions on GPU
Stefano Carrazza, Juan M. Cruz-Martinez, Marco Rossi
We present PDFFlow, a new software for fast evaluation of parton distribution functions (PDFs) designed for platforms with hardware accelerators. PDFs are essential for the calcula…