Flexible Spectral-Normalized Neural Gaussian Process for Dynamic Aperture Prediction
The proposed empirical Bayes framework offers a general solution for training heteroscedastic neural models in situations where manual hyperparameter tuning is impractical, and it is anticipated that this framework can be applied to other domains that encounter comparable computational limitations.
Yousra El-Bachir, F. F. Van der Veken, D. Di Croce et al.
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