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Found 5 papers, 1 papers with code
The LHCb ultra-fast simulation option, Lamarr: design and validation
In this context, we propose Lamarr, a Gaudi-based framework designed to offer the fastest solution for the simulation of the LHCb detector.
Hyperparameter Optimization as a Service on INFN Cloud
In this contribution we discuss how a set of RestAPIs can be used to access a dedicated service based on INFN Cloud to monitor and possibly coordinate multiple training instances, with gradient-less optimization techniques, via simple HTTP requests.
Generative models uncertainty estimation
In recent years fully-parametric fast simulation methods based on generative models have been proposed for a variety of high-energy physics detectors.
Towards Reliable Neural Generative Modeling of Detectors
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 produced.
Fast Data-Driven Simulation of Cherenkov Detectors Using Generative Adversarial Networks
The increasing luminosities of future Large Hadron Collider runs and next generation of collider experiments will require an unprecedented amount of simulated events to be produced.
