Quantifying SARS‐CoV‐2 infection risk within the Google/Apple Exposure Notification framework to inform quarantine recommendations AM Wilson, N Aviles, JI Petrie, PI Beamer, Z Szabo, M Xie, J McIllece, ... Risk Analysis 42 (1), 162-176, 2022 | 29 | 2022 |
Slowing the Spread of Infectious Diseases Using Crowdsourced Data HX Sydney Von Arx, Isaiah Becker-Mayer, Daniel Blank, Jesse Colligan, Rhys ... https://www.covid-watch.org/covid_watch_whitepaper.pdf, 2020 | 20* | 2020 |
Fast neural network predictions from constrained aerodynamics datasets C White, D Ushizima, C Farhat AIAA Scitech 2020 Forum, 0364, 2020 | 20 | 2020 |
Neural networks predict fluid dynamics solutions from tiny datasets C White, D Ushizima, C Farhat arXiv preprint arXiv:1902.00091, 2019 | 20 | 2019 |
Space‐local reduced‐order bases for accelerating reduced‐order models through sparsity S Anderson, C White, C Farhat International Journal for Numerical Methods in Engineering 124 (7), 1646-1671, 2023 | 4 | 2023 |
A clustering algorithm for reduced order modeling of shock waves TR White technical report, Department of Mechanical Engineering, Stanford University, 2015 | 3 | 2015 |
The utility of hysteresis for closed-loop control applications that maintain attached flow under natural post stall conditions on airfoils B Zakharin, P Tewes, C Chen, I Wygnanski, A Washburn 4th Flow Control Conference, 4078, 2008 | 3 | 2008 |
Flutter-resistant turbomachinery blades C White US Patent 9784286B2, 2017 | | 2017 |
Flutter-resistant transonic turbomachinery blades and methods for reducing transonic turbomachinery blade flutter C White US Patent 20150233390A1, 2015 | | 2015 |
Flutter-resistant transonic turbomachinery blades and methods for reducing transonic turbomachinery blade flutter C White EP Patent 2907972A1, 2014 | | 2014 |
Application of Computational Fluid Dynamics on a Blunt Elliptical Airfoil C Bhamburkar University of Arizona, 2009 | | 2009 |
What can neural networks learn about flow physics? T White | | |
A neural network architecture for reduced order modeling of PDEs T White | | |