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Found 3 papers, 2 papers with code
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification
On the other hand, we show that training with domain adaptation improves model robustness and mitigates the effects of these perturbations, improving the classification accuracy by 23% on data with higher observational noise.
BOOSTR: A Dataset for Accelerator Control Systems
The Booster Operation Optimization Sequential Time-series for Regression (BOOSTR) dataset was created to provide a cycle-by-cycle time series of readings and settings from instruments and controllable devices of the Booster, Fermilab's Rapid-Cycling Synchrotron (RCS) operating at 15~Hz.
Anomaly Detection
Time Series Analysis
Accelerator Physics
Systems and Control
Systems and Control
Real-time Artificial Intelligence for Accelerator Control: A Study at the Fermilab Booster
We describe a method for precisely regulating the gradient magnet power supply at the Fermilab Booster accelerator complex using a neural network trained via reinforcement learning.
Accelerator Physics
