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ORCIDMajdi I. Radaideh
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2020 – today
- 2024
[j7]Steven Goldenberg
, Malachi Schram, Kishansingh Rajput, Thomas Britton, Chris Pappas, Dan Lu, Jared Walden, Majdi I. Radaideh, Sarah Cousineau, Sudarshan Harave:
Distance preserving machine learning for uncertainty aware accelerator capacitance predictions. Mach. Learn. Sci. Technol. 5(4): 45009 (2024)- [i8]Majdi I. Radaideh, Leo Tunkle, Dean Price, Kamal Abdulraheem, Linyu Lin, Moutaz Elias:
Multistep Criticality Search and Power Shaping in Microreactors with Reinforcement Learning. CoRR abs/2406.15931 (2024) - 2023
- [j6]Dean Price, Majdi I. Radaideh:
Animorphic ensemble optimization: a large-scale island model. Neural Comput. Appl. 35(4): 3221-3243 (2023) - [i7]Yasir Alanazi, Malachi Schram, Kishansingh Rajput, Steven Goldenberg, Lasitha Vidyaratne, Chris Pappas, Majdi I. Radaideh, Dan Lu, Pradeep Ramuhalli, Sarah Cousineau:
Multi-module based CVAE to predict HVCM faults in the SNS accelerator. CoRR abs/2304.10639 (2023) - [i6]Steven Goldenberg, Malachi Schram, Kishansingh Rajput, Thomas Britton, Chris Pappas, Dan Lu, Jared Walden, Majdi I. Radaideh, Sarah Cousineau, Sudarshan Harave:
Distance Preserving Machine Learning for Uncertainty Aware Accelerator Capacitance Predictions. CoRR abs/2307.02367 (2023) - [i5]Veda Joynt, Jacob Cooper, Naman Bhargava, Katie Vu, O. Hwang Kwon, Todd R. Allen, Aditi Verma, Majdi I. Radaideh:
A Comparative Analysis of Text-to-Image Generative AI Models in Scientific Contexts: A Case Study on Nuclear Power. CoRR abs/2312.01180 (2023) - 2022
- [j5]Majdi I. Radaideh, Chris Pappas, Jared Walden, Dan Lu, Lasitha Vidyaratne, Thomas Britton, Kishansingh Rajput, Malachi Schram, Sarah Cousineau:
Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders. Digit. Signal Process. 130: 103704 (2022) - [i4]Majdi I. Radaideh, Hoang Tran, Lianshan Lin, Hao Jiang, Drew Winder, Sarma Gorti, Guannan Zhang, Justin Mach, Sarah Cousineau:
Model Calibration of the Liquid Mercury Spallation Target using Evolutionary Neural Networks and Sparse Polynomial Expansions. CoRR abs/2202.09353 (2022) - [i3]Majdi I. Radaideh, Chris Pappas, Mark Wezensky, Pradeep Ramuhalli, Sarah Cousineau:
Fault Prognosis in Particle Accelerator Power Electronics Using Ensemble Learning. CoRR abs/2209.15570 (2022) - 2021
- [j4]Majdi I. Radaideh, Koroush Shirvan:
Rule-based reinforcement learning methodology to inform evolutionary algorithms for constrained optimization of engineering applications. Knowl. Based Syst. 217: 106836 (2021) - [i2]Majdi I. Radaideh, Katelin Du, Paul Seurin, Devin Seyler, Xubo Gu, Haijia Wang, Koroush Shirvan:
NEORL: NeuroEvolution Optimization with Reinforcement Learning. CoRR abs/2112.07057 (2021) - 2020
- [j3]Majdi I. Radaideh, Connor Pigg, Tomasz Kozlowski, Yujia Deng, Annie Qu:
Neural-based time series forecasting of loss of coolant accidents in nuclear power plants. Expert Syst. Appl. 160: 113699 (2020) - [j2]Majdi I. Radaideh, Tomasz Kozlowski:
Surrogate modeling of advanced computer simulations using deep Gaussian processes. Reliab. Eng. Syst. Saf. 195: 106731 (2020) - [i1]Majdi I. Radaideh, Koroush Shirvan:
Improving Intelligence of Evolutionary Algorithms Using Experience Share and Replay. CoRR abs/2009.08936 (2020)
2010 – 2019
- 2019
- [j1]Majdi I. Radaideh, Katarzyna Borowiec, Tomasz Kozlowski:
Integrated framework for model assessment and advanced uncertainty quantification of nuclear computer codes under Bayesian statistics. Reliab. Eng. Syst. Saf. 189: 357-377 (2019)
Coauthor Index
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