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07/05/2023
Distance Preserving Machine Learning for Uncertainty Aware Accelerator Capacitance Predictions
Providing accurate uncertainty estimations is essential for producing re...
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04/20/2023
Multi-module based CVAE to predict HVCM faults in the SNS accelerator
We present a multi-module framework based on Conditional Variational Aut...
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09/30/2022
Fault Prognosis in Particle Accelerator Power Electronics Using Ensemble Learning
Early fault detection and fault prognosis are crucial to ensure efficien...
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02/18/2022
Model Calibration of the Liquid Mercury Spallation Target using Evolutionary Neural Networks and Sparse Polynomial Expansions
The mercury constitutive model predicting the strain and stress in the t...
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02/08/2022
Bayesian Inverse Uncertainty Quantification of the Physical Model Parameters for the Spallation Neutron Source First Target Station
The reliability of the mercury spallation target is mission-critical for...
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12/01/2021
NEORL: NeuroEvolution Optimization with Reinforcement Learning
We present an open-source Python framework for NeuroEvolution Optimizati...
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08/10/2020
Improving Intelligence of Evolutionary Algorithms Using Experience Share and Replay
We propose PESA, a novel approach combining Particle Swarm Optimisation ...
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01/17/2019