Classifier-pruned Bayesian optimization for particle accelerator tuning: Exploring temporally structured manifold of 6D beam phase space

arXiv:2412.01748 · cs.LG · Submitted 2024-12-02 · Read on arXiv

cs.LG

Submitted: 2024-12-02

Updated: 2026-09-27

Terminology

• Latent Space — 37× in this paper · explained in 7 episodes
• Bayesian Optimization — 26× in this paper · explained in 3 episodes
• Latent Representation — 5× in this paper · explained in 2 episodes
• Pruning — 5× in this paper · explained in 4 episodes
• Acquisition Function — 4× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Bayesian Optimization (BO) — 3× in this paper · explained in 3 episodes
• Gaussian Process — 3× in this paper
• Random Search — 3× in this paper
• Action Space — 2× in this paper · explained in 1 episode
• Decode — 2× in this paper · explained in 2 episodes
• Expected Improvement — 2× in this paper
• Fidelity — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Active Learning — 1× in this paper · explained in 6 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Inverse Design — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Multi-objective Optimization — 1× in this paper · explained in 4 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• System Identification — 1× in this paper · explained in 3 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Prior-mean-assisted Bayesian optimization application on FRIB Front-End tunning
• Auto-Encoding Variational Bayes
• Mahalanobis-Guided Latent OOD Detection for Hybrid ES-DRL Control in Time-Varying Systems
• Improved Robustness of Deep Reinforcement Learning for Control of Time-Varying Systems by Bounded Extremum Seeking
• cDVAE: Multimodal Generative Conditional Diffusion Guided by Variational Autoencoder Latent Embedding for Virtual 6D Phase Space Diagnostics

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