NLO QCD corrections to SM-EFT dilepton and electroweak Higgs boson production, matched to parton shower in POWHEG S Alioli, W Dekens, M Girard, E Mereghetti Journal of High Energy Physics 2018 (8), 1-42, 2018 | 70 | 2018 |
Evaluation of deep learning architectures for aqueous solubility prediction G Panapitiya, M Girard, A Hollas, J Sepulveda, V Murugesan, W Wang, ... ACS omega 7 (18), 15695-15710, 2022 | 32 | 2022 |
Uranium oxide synthetic pathway discernment through unsupervised morphological analysis M Girard, A Hagen, I Schwerdt, M Gaumer, L McDonald, N Hodas, ... Journal of Nuclear Materials 552, 152983, 2021 | 15 | 2021 |
Predicting aqueous solubility of organic molecules using deep learning models with varied molecular representations G Panapitiya, M Girard, A Hollas, V Murugesan, W Wang, E Saldanha arXiv preprint arXiv:2105.12638, 2021 | 7 | 2021 |
Digital signal processing using deep neural networks B Shevitski, Y Watkins, N Man, M Girard arXiv preprint arXiv:2109.10404, 2021 | 5 | 2021 |
Deep Learning for Spectral Filling in Radio Frequency Applications M Setzler, E Coda, J Rounds, M Vann, M Girard 2022 Sensor Signal Processing for Defence Conference (SSPD), 1-5, 2022 | 1 | 2022 |
Universal Fourier Attack for Time Series CN DeSmet, MK Girard, ED Coda, YZ Watkins Pacific Northwest National Laboratory (PNNL), Richland, WA (United States), 2023 | | 2023 |
Universal Fourier Attack for Time Series E Coda, B Clymer, C DeSmet, Y Watkins, M Girard arXiv preprint arXiv:2209.00757, 2022 | | 2022 |
Towards Precision Standard Model Calculations M Girard University of California, Berkeley, 2018 | | 2018 |