| Sevir: A storm event imagery dataset for deep learning applications in radar and satellite meteorology M Veillette, S Samsi, C Mattioli Advances in Neural Information Processing Systems 33, 22009-22019, 2020 | 142 | 2020 |
| Properties and numerical evaluation of the Rosenblatt distribution MS Veillette, MS Taqqu | 107 | 2013 |
| STBL: Alpha stable distributions for MATLAB M Veillette Matlab Central File Exchange, retreived October 10, 2012, 2012 | 69* | 2012 |
| Numerical computation of first-passage times of increasing Lévy processes M Veillette, MS Taqqu Methodology and Computing in Applied Probability 12 (4), 695-729, 2010 | 45 | 2010 |
| Using differential equations to obtain joint moments of first-passage times of increasing Lévy processes M Veillette, MS Taqqu Statistics & probability letters 80 (7-8), 697-705, 2010 | 41 | 2010 |
| Creating synthetic radar imagery using convolutional neural networks MS Veillette, EP Hassey, CJ Mattioli, H Iskenderian, PM Lamey Journal of Atmospheric and Oceanic Technology 35 (12), 2323-2338, 2018 | 33 | 2018 |
| Heterogeneous convective weather forecast translation into airspace permeability with prediction intervals MP Matthews, MS Veillette, JC Venuti, RA DeLaura, JK Kuchar Journal of Air Transportation 24 (2), 41-54, 2016 | 32 | 2016 |
| Distributed deep learning for precipitation nowcasting S Samsi, CJ Mattioli, MS Veillette 2019 IEEE High Performance Extreme Computing Conference (HPEC), 1-7, 2019 | 30 | 2019 |
| Graphical display of radar and radar-like meteorological data MS Veillette, MM Wolfson, H Iskenderian, C Mattioli, ER Williams US Patent App. 14/290,308, 2014 | 24 | 2014 |
| Pce-pinns: Physics-informed neural networks for uncertainty propagation in ocean modeling B Lütjens, CH Crawford, M Veillette, D Newman arXiv preprint arXiv:2105.02939, 2021 | 21 | 2021 |
| A technique for computing the PDFs and CDFs of nonnegative infinitely divisible random variables MS Veillette, MS Taqqu Journal of applied probability 48 (1), 217-237, 2011 | 19 | 2011 |
| Polarimetric observations of chaff using the WSR-88D network JM Kurdzo, ER Williams, DJ Smalley, BJ Bennett, DC Patterson, ... Journal of Applied Meteorology and Climatology 57 (5), 1063-1081, 2018 | 12 | 2018 |
| Airspace Flow Rate Forecast Algorithms, Validation, and Implementation M Matthews, R DeLaura, M Veillette, J Venuti, J Kuchar Project report atc-428, MIT Lincoln Laboratory, Lexington, MA, 2015 | 9 | 2015 |
| Adapting deep learning models to new meteorological contexts using transfer learning P Khorrami, O Simek, B Cheung, M Veillette, R Dangovski, I Rugina, ... 2021 IEEE International conference on big data (Big Data), 4169-4177, 2021 | 7 | 2021 |
| The offshore precipitation capability M Veillette, H Iskenderian, M Wolfson, C Mattioli, E Hassey, P Lamey Project Report ATC-430, MIT Lincoln Laboratory, Lexington, MA, 2016 | 7 | 2016 |
| Serving machine learning inference using heterogeneous hardware B Li, V Gadepally, S Samsi, M Veillette, D Tiwari 2021 IEEE High Performance Extreme Computing Conference (HPEC), 1-8, 2021 | 6 | 2021 |
| Compute, time and energy characterization of encoder-decoder networks with automatic mixed precision training S Samsi, M Jones, MM Veillette 2020 IEEE High Performance Extreme Computing Conference (HPEC), 1-6, 2020 | 6 | 2020 |
| Translating Convective Weather Forecasts into Strategic Traffic Management Decision Aids M Matthews, M Veillette, J Venuti, R DeLaura, J Kuchar 12th USA/Europe Air Traffic Management Research and Development Seminar, 2017 | 6 | 2017 |
| Convective initiation forecasts through the use of machine learning methods MS Veillette, H Iskenderian, PM Lamey, LJ Bickmeier 93rd American Meteorological Society Annual Meeting: 16th Conference on …, 2013 | 6 | 2013 |
| A deep learning–based velocity dealiasing algorithm derived from the WSR-88D open radar product generator MS Veillette, JM Kurdzo, PM Stepanian, J McDonald, S Samsi, JYN Cho Artificial Intelligence for the Earth Systems 2 (3), e220084, 2023 | 5 | 2023 |
