no code implementations • 28 Dec 2021 • Aleksandra Ćiprijanović, Diana Kafkes, Gregory Snyder, F. Javier Sánchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild
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.
1 code implementation • 20 Jan 2021 • Diana Kafkes, Jason St. John
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
1 code implementation • 14 Nov 2020 • Jason St. John, Christian Herwig, Diana Kafkes, William A. Pellico, Gabriel N. Perdue, Andres Quintero-Parra, Brian A. Schupbach, Kiyomi Seiya, Nhan Tran, Javier M. Duarte, Yunzhi Huang, Malachi Schram, Rachael Keller
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