Continual Learning for Particle Accelerators
Unfortunately, I could not travel to the conference, thanks to Malachi Schram for presenting this spotlight Talk on our paper "Continual Learning for Particle Accelerators"
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December 6, 2025 12:00 AM — 12:00 AM
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1 min read
Towards a Robust Adaptive Digital Twin for Fusion Applications
Talk Talk on developing robust adaptive digital twins with uncertainty awareness for fusion science applications.
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Differential and Explainable Reinforcement Learning for Multi-objective Optimization in Particle Accelerators
Invited Talk Explainable and Differential Reinforcement Learning for Multi-objective Optimization in Particle Accelerators
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Towards continual machine learning for your ever-changing accelerators
Invited Talk Continual/Lifelong machine learning for ever drifting particle accelerator data at IBIC 2025, University of Liverpool, UK.
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Harnessing the Power of Gradient Based Simulations for Multi-Objective Optimization in Particle Accelerators
Invited Talk Talk on applying fast optimization and control with differential reinforcement learning leveraging differential simulations.
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Multi-objective Reinforcement Learning
Invited Lecture Lecture on Multi-objective Reinforcement Learning as applied to Particle Accelerators at MaLAPA 2025, CERN, Geneva.
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Errant Beam Prognostics with Machine Leaning at SNS Accelerator
Invited Talk Talk on application of conditional machine learning models to predict anomalies before they occur at SNS accelerator.
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Composable Optimization and Control Toolkit for Scientific Applications
Invited Talk Long term software steward requires composable modular development and management.
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Machine Learning for Prognostics and Optimization of Particle Accelerators
Invited Talk Current progress on machine learning applications for particle accelerators and its scope for Fusion Science.
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Fault Prediction in Particle Accelerators
Guest Lecture Guest lecture within the graduate particle accelerators class at ODU department of physics.
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Machine Learning to Improve Accelerator Operation at SNS
Invited Talk Application of Machine Learning to improve accelerator operation, application of conditional models to predict anomalies at SNS accelerator.
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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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Uncertainty Quantification for Rare Events in Scientific Applications
Uncertainty Quantification for Rare Events (Out-of-Distribution Detection) via Gaussian Process Approximation in Scientific Applications
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Anomaly Detection and Online Data Quality Monitoring
Online data quality monitoring with ML (Hydra) and Anomaly Detection on streaming data from physics and particle accelerator experiments.
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Hydra - Layer-wise Relevance Propagation
Potential applications of explainable ML techniques such as Layer-wise relevance propagation in Medical Sciences
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