5 citations · 8 across the 6 of their papers we have counts for
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physics.acc-ph2021★ 1 cited
Developing Robust Digital Twins and Reinforcement Learning for Accelerator Control Systems at the Fermilab Booster
D. Kafkes, M. Schram
We describe the offline machine learning (ML) development for an effort to precisely regulate the Gradient Magnet Power Supply (GMPS) at the Fermilab Booster accelerator complex vi…
physics.acc-ph2021
Accelerator Real-time Edge AI for Distributed Systems (READS) Proposal
K. Seiya, K. J. Hazelwood, M. A. Ibrahim +7
Our objective will be to integrate ML into Fermilab accelerator operations and furthermore provide an accessible framework which can also be used by a broad range of other accelera…