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Distance Preserving Machine Learning for Uncertainty Aware Accelerator Capacitance Predictions

Distance Preserving Machine Learning for Uncertainty Aware Accelerator Capacitance Predictions

S. Goldenberg
M. Schram
Kishansingh Rajput
T. Britton
C. Pappas
Dawei Lu
Jared Walden
M. Radaideh
Sarah Cousineau
S. Harave
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Papers citing "Distance Preserving Machine Learning for Uncertainty Aware Accelerator Capacitance Predictions"

2 / 2 papers shown
Title
Robust Errant Beam Prognostics with Conditional Modeling for Particle Accelerators
Robust Errant Beam Prognostics with Conditional Modeling for Particle Accelerators
Kishansingh Rajput
Malachi Schram
Willem Blokland
Yasir Alanazi
Pradeep Ramuhalli
Alexander Zhukov
Charles Peters
Ricardo Vilalta
30
5
0
22 Nov 2023
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,145
0
06 Jun 2015