| Uncovering turbulent plasma dynamics via deep learning from partial observations A Mathews, M Francisquez, JW Hughes, DR Hatch, B Zhu, BN Rogers Physical Review E 104 (2), 025205, 2021 | 75 | 2021 |
| A simple relationship for the spectro-temporal structure of bursts from FRB 121102 F Rajabi, MA Chamma, CM Wyenberg, A Mathews, M Houde Monthly Notices of the Royal Astronomical Society 498 (4), 4936-4942, 2020 | 35 | 2020 |
| Explaining fast radio bursts through Dicke's superradiance M Houde, A Mathews, F Rajabi Monthly Notices of the Royal Astronomical Society 475 (1), 514-522, 2018 | 34 | 2018 |
| Triggered superradiance and fast radio bursts M Houde, F Rajabi, BM Gaensler, A Mathews, V Tranchant Monthly Notices of the Royal Astronomical Society 482 (4), 5492-5499, 2019 | 24 | 2019 |
| Evidence of a shared spectro-temporal law between sources of repeating fast radio bursts MA Chamma, F Rajabi, CM Wyenberg, A Mathews, M Houde Monthly Notices of the Royal Astronomical Society 507 (1), 246-260, 2021 | 23 | 2021 |
| Validation of 2D and measurements made with Helium imaging spectroscopy in the volume of the TCV divertor BL Linehan, A Perek, BP Duval, F Bagnato, P Blanchard, C Colandrea, ... Nuclear Fusion 63 (3), 036021, 2023 | 14 | 2023 |
| Quantifying experimental edge plasma evolution via multidimensional adaptive Gaussian process regression A Mathews, J Hughes IEEE Transactions on Plasma Science 49 (12), 3841 - 3847, 2021 | 10 | 2021 |
| Uncovering turbulent plasma dynamics via deep learning from partial observations A Mathews, M Francisquez, J Hughes, D Hatch, B Zhu, B Rogers arXiv preprint arXiv:2009.05005, 2020 | 9* | 2020 |
| The role of superradiance in cosmic fast radio bursts A Mathews The University of Western Ontario, 2017 | 9 | 2017 |
| Turbulent field fluctuations in gyrokinetic and fluid plasmas A Mathews, N Mandell, M Francisquez, JW Hughes, A Hakim Physics of Plasmas 28 (11), 2021 | 8 | 2021 |
| Deep Electric Field Predictions by Drift-Reduced Braginskii Theory with Plasma-Neutral Interactions Based on Experimental Images of Boundary Turbulence A Mathews, JW Hughes, JL Terry, SG Baek Physical Review Letters 129 (23), 235002, 2022 | 7 | 2022 |
| Deep modeling of plasma and neutral fluctuations from gas puff turbulence imaging A Mathews, JL Terry, SG Baek, JW Hughes, AQ Kuang, B LaBombard, ... Review of Scientific Instruments 93 (6), 2022 | 6 | 2022 |
| Confinement regime identification on Alcator C-Mod using supervised machine learning methods A Mathews, JW Hughes, AE Hubbard, DG Whyte, SM Wolfe, ... MIT-PSFC Internal Report, 2019 | 3 | 2019 |
| Physics-informed machine learning techniques for edge plasma turbulence modelling in computational theory and experiment A Mathews arXiv preprint arXiv:2205.07838, 2022 | 2 | 2022 |
| Experimental research on the TCV tokamak BP Duval, A Abdolmaleki, M Agostini, CJ Ajay, S Alberti, E Alessi, ... Nuclear Fusion 64 (11), 112023, 2024 | 1 | 2024 |
| A shared law between sources of repeating fast radio bursts MA Chamma, F Rajabi, CM Wyenberg, A Mathews, M Houde arXiv preprint arXiv:2010.14041, 2020 | 1 | 2020 |
| The edge pedestal on the SPARC tokamak JW Hughes, NT Howard, M Greenwald, AE Hubbard, A Mathews, ... APS Division of Plasma Physics Meeting Abstracts 2019, CO5. 006, 2019 | 1 | 2019 |
| Impacts of first-and second-order optimization in deep learning of turbulent fluctuations from gas puff imaging A Mathews Journal of Physics: Conference Series 2397 (1), 012001, 2022 | | 2022 |
| Deep electric field predictions by drift-reduced Braginskii theory with plasma-neutral interactions based upon experimental images of boundary turbulence A Mathews, J Hughes, J Terry, SG Baek arXiv preprint arXiv:2204.11689, 2022 | | 2022 |
| Differences in binarity between gluon and graviton scattering amplitudes A Mathews arXiv preprint arXiv:1912.05152, 2019 | | 2019 |
