Brian Nord
Orcid: 0000-0001-6706-8972
According to our database1,
Brian Nord
authored at least 34 papers
between 2016 and 2023.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2023
Mach. Learn. Sci. Technol., June, 2023
DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection.
Mach. Learn. Sci. Technol., June, 2023
Self-Driving Telescopes: Autonomous Scheduling of Astronomical Observation Campaigns with Offline Reinforcement Learning.
CoRR, 2023
Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets.
CoRR, 2023
Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers.
CoRR, 2023
2022
Mach. Learn. Sci. Technol., December, 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
Discovering the building blocks of dark matter halo density profiles with neural networks.
CoRR, 2022
Learning Representation for Bayesian Optimization with Collision-free Regularization.
CoRR, 2022
DeepGhostBusters: Using Mask R-CNN to detect and mask ghosting and scattered-light artifacts from optical survey images.
Astron. Comput., 2022
2021
PLoS Comput. Biol., 2021
Deeply uncertain: comparing methods of uncertainty quantification in deep learning algorithms.
Mach. Learn. Sci. Technol., 2021
J. Open Source Softw., 2021
CoRR, 2021
DeepMerge II: Building Robust Deep Learning Algorithms for Merging Galaxy Identification Across Domains.
CoRR, 2021
CoRR, 2021
A machine learning approach to the detection of ghosting and scattered light artifacts in dark energy survey images.
Astron. Comput., 2021
2020
CoRR, 2020
Astron. Comput., 2020
Proceedings of the NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 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
CoRR, 2019
DeepCMB: Lensing reconstruction of the cosmic microwave background with deep neural networks.
Astron. Comput., 2019
Proceedings of the 2019 IEEE International Conference on Big Data, 2019
2016
Astron. Comput., 2016