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Found 4 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.
Lamarr: LHCb ultra-fast simulation based on machine learning models deployed within Gauss
The needed simulation will far exceed the pledged resources, requiring an evolution in technologies and techniques to produce these simulated data samples.
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.
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.
