Towards continual machine learning for particle accelerators
This paper presents results from ongoing efforts to develop continual learning methods for particle accelerators. We address the challenge of model adaptation to changing …
rajput-k.
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An Outlook Towards Deployable Continual Learning for Particle Accelerators
Particle accelerators rely on the precise synchronization of thousands of components, but data distribution drifts often limit the long-term deployment of machine learning …
rajput-k.
Robust errant beam prognostics with conditional modeling for particle accelerators
Conditional Models to handle data drifts due to changes in beam configuration changes at SNS accelerator.
rajput-k.
Model up-keep with Continual Learning for Particle Accelerators
Invited Tutorial Lecture on Model up-keep / Continual Learning for Particle Accelerators at MaLAPA 2024, Gyeongju, South Korea.
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