Gabriel N. Perdue

Orcid: 0000-0001-6785-8720

According to our database1, Gabriel N. Perdue authored at least 19 papers between 2017 and 2024.

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Bibliography

2024
Artificial Intelligence for the Electron Ion Collider (AI4EIC).
Comput. Softw. Big Sci., December, 2024

Quantum circuit fidelity estimation using machine learning.
Quantum Mach. Intell., June, 2024

2023
DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection.
Mach. Learn. Sci. Technol., June, 2023

Artificial Intelligence for the Electron Ion Collider (AI4EIC).
CoRR, 2023

2022
DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification.
Mach. Learn. Sci. Technol., 2022

Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection.
CoRR, 2022

Neural network accelerator for quantum control.
CoRR, 2022

2021
Quantum machine learning in high energy physics.
Mach. Learn. Sci. Technol., 2021

Robustness of deep learning algorithms in astronomy - galaxy morphology studies.
CoRR, 2021

DeepMerge II: Building Robust Deep Learning Algorithms for Merging Galaxy Identification Across Domains.
CoRR, 2021

2020
Domain adaptation techniques for improved cross-domain study of galaxy mergers.
CoRR, 2020

2019
Restricted Boltzmann Machines for galaxy morphology classification with a quantum annealer.
CoRR, 2019

Response to NITRD, NCO, NSF Request for Information on "Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan".
CoRR, 2019

Inferring Convolutional Neural Networks' Accuracies from Their Architectural Characterizations.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Deep Learning for Vertex Reconstruction of Neutrino-nucleus Interaction Events with Combined Energy and Time Data.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Machine Learning in High Energy Physics Community White Paper.
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CoRR, 2018

2017
Evolving Deep Networks Using HPC.
Proceedings of the Machine Learning on HPC Environments, 2017

Neuromorphic computing for temporal scientific data classification.
Proceedings of the Neuromorphic Computing Symposium, 2017

Vertex reconstruction of neutrino interactions using deep learning.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017


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