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PDFFlow: hardware accelerating parton density access

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 calculation of particle physics observables through Monte Carlo simulation …

VegasFlow: accelerating Monte Carlo simulation across platforms

In this work we demonstrate the usage of the VegasFlow library on multidevice situations: multi-GPU in one single node and multi-node in a cluster. VegasFlow is a new software for fast evaluation of highly parallelizable integrals based on Monte …

Constructing PineAPPL grids on hardware accelerators

Studying the parton content of the proton with deep learning models

libGroomRL: Reinforcement Learning for Jets

Modelling conditional probabilities with Riemann-Theta Boltzmann Machines

Towards hardware acceleration for parton densities estimation

Machine Learning in High Energy Physics Community White Paper

Machine learning challenges in theoretical HEP

Minimisation strategies for the determination of parton density functions