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 accelerator conditions while maintaining backward compatibility with existing control systems.

Proceedings of IBIC 2025 - 14th International Beam Instrumentation Conference, JACoW Publishing