| An application of deep learning in the analysis of stellar spectra S Fabbro, KA Venn, T O'Briain, S Bialek, CL Kielty, F Jahandar, S Monty Monthly Notices of the Royal Astronomical Society 475 (3), 2978-2993, 2018 | 127 | 2018 |
| Cycle-starnet: Bridging the gap between theory and data by leveraging large data sets T O’Briain, YS Ting, S Fabbro, MY Kwang, K Venn, S Bialek The Astrophysical Journal 906 (2), 130, 2021 | 34 | 2021 |
| Assessing the performance of LTE and NLTE synthetic stellar spectra in a machine learning framework S Bialek, S Fabbro, KA Venn, N Kumar, T O’Briain, KM Yi Monthly Notices of the Royal Astronomical Society 498 (3), 3817-3834, 2020 | 24 | 2020 |
| Stellar Parameters and Chemical Abundances Estimated from LAMOST-II DR8 MRS Based on Cycle-StarNet R Wang, AL Luo, S Zhang, YS Ting, T O’Briain, Lamost Mrs Collaboration The Astrophysical Journal Supplement Series 266 (2), 40, 2023 | 4 | 2023 |
| Synthesizing of lung tumors in computed tomography images TB O'Briain, KM Yi, M Bazalova‐Carter Medical Physics 47 (10), 5070-5076, 2020 | 4 | 2020 |
| Starnet: A deep learning analysis of infrared stellar spectra CL Kielty, S Bialek, S Fabbro, KA Venn, T O'Briain, F Jahandar, S Monty Software and cyberinfrastructure for astronomy v 10707, 814-824, 2018 | 4 | 2018 |
| FlowNet-PET: unsupervised learning to perform respiratory motion correction in PET imaging T O'Briain, C Uribe, KM Yi, J Teuwen, I Sechopoulos, M Bazalova-Carter arXiv preprint arXiv:2205.14147, 2022 | 2 | 2022 |
| Interpreting Stellar Spectra with Unsupervised Domain Adaptation T O'Briain, YS Ting, S Fabbro, KM Yi, K Venn, S Bialek arXiv preprint arXiv:2007.03112, 2020 | 2 | 2020 |
| Publicly available framework for simulating and experimentally validating clinical PET systems TB O'Briain, C Uribe, I Sechopoulos, C Michel, M Bazalova‐Carter Medical physics 50 (3), 1549-1559, 2023 | 1 | 2023 |
| Unsupervised learning to perform respiratory motion correction in PET imaging T O'Briain, C Uribe, I Sechopoulos, KM Yi, J Teuwen, M Bazalova-Carter Journal of Nuclear Medicine 63 (supplement 2), 2401-2401, 2022 | 1 | 2022 |
| StarNet: An application of deep learning in the analysis of stellar spectra C Kielty, S Bialek, S Fabbro, K Venn, T O'Briain, F Jahandar, S Monty American Astronomical Society Meeting Abstracts# 232 232, 223.09, 2018 | 1 | 2018 |
| An Application of Deep Neural Networks in the Analysis of Stellar Spectra S Fabbro, K Venn, T O'Briain, S Bialek, C Kielty, F Jahandar, S Monty arXiv preprint arXiv:1709.09182, 2017 | 1 | 2017 |
| Half a Million M Dwarf Stars Characterized Using Domain-Adapted Spectral Analysis S Zhang, HW Zhang, YS Ting, R Wang, T O'Briain, HRA Jones, ... arXiv preprint arXiv:2502.01910, 2025 | | 2025 |
| VizieR Online Data Catalog: Stellar parameters from LAMOST MRS DR8 (Wang+, 2023) R Wang, AL Luo, S Zhang, YS Ting, T O'Briain, Lamost Mrs Collaboration VizieR Online Data Catalog 226, J/ApJS/266/40, 2023 | | 2023 |
| Correcting for Patient Breathing Motion in PET Imaging T O'Briain | | 2022 |
| Optimization of [18F] FDG Injected Activity for a New GE Discovery MI PET/CT Scanner Using a NEMA Phantom A Hart, T O'Briain, M Bazalova-Carter, A Rahmim, W Beckham, ... MEDICAL PHYSICS 47 (6), E545-E545, 2020 | | 2020 |
| Stellar Parameters with Deep Learning S Fabbro, K Venn, T O'Briain, S Bialek, C Kielty, F Jahandar, S Monty Astronomical Data Analysis Software and Systems XXVII 522, 393, 2020 | | 2020 |
| Reducing the Human Effort in Developing PET-CT Registration T O'Briain, KH Jin, H Choi, E Chin, M Bazalova-Carter, KM Yi arXiv preprint arXiv:1911.10657, 2019 | | 2019 |
