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pro vyhledávání: '"Howell, Michael A."'
Autor:
Tsai, Peng-Hung, Berleant, Daniel, Segall, Richard S., Aboudja, Hyacinthe, Batthula, Venkata Jaipal R., Duggirala, Sheela, Howell, Michael
Publikováno v:
International Journal of Innovation and Technology Management (2023), 20(4):2330002
Quantitative technology forecasting uses quantitative methods to understand and project technological changes. It is a broad field encompassing many different techniques and has been applied to a vast range of technologies. A widely used approach in
Externí odkaz:
http://arxiv.org/abs/2401.02549
Autor:
Fan, Yangxin, Yu, Xuanji, Wieser, Raymond, Meakin, David, Shaton, Avishai, Jaubert, Jean-Nicolas, Flottemesch, Robert, Howell, Michael, Braid, Jennifer, Bruckman, Laura S., French, Roger, Wu, Yinghui
The integration of the global Photovoltaic (PV) market with real time data-loggers has enabled large scale PV data analytical pipelines for power forecasting and long-term reliability assessment of PV fleets. Nevertheless, the performance of PV data
Externí odkaz:
http://arxiv.org/abs/2302.10860
Publikováno v:
The Space Review (2019), Jan. 7, www.thespacereview.com/article/3632/1
Technologies have often been observed to improve exponentially over time. In practice this often means identifying a constant known as the doubling time, describing the time period over which the technology roughly doubles in some measure of performa
Externí odkaz:
http://arxiv.org/abs/2107.09637
Autor:
Howell, Michael D., Kuo, Fiona I., Rumberger, Beth, Boarder, Erika, Sun, Kang, Butler, Kathleen, Harris, John E., Grimes, Pearl, Rosmarin, David
Publikováno v:
In JID Innovations November 2023 3(6)
Akademický článek
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Akademický článek
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Autor:
Fischer, Felix, Doll, Anais, Uereyener, Deniz, Roenneberg, Sophie, Hillig, Christina, Weber, Lucca, Hackert, Verena, Meinel, Martin, Farnoud, Ali, Seiringer, Peter, Thomas, Jenny, Anand, Philipp, Graner, Larissa, Schlenker, Franziska, Zengerle, Roland, Jonsson, Pontus, Jargosch, Manja, Theis, Fabian J., Schmidt-Weber, Carsten B., Biedermann, Tilo, Howell, Michael, Reich, Kristian, Eyerich, Kilian, Menden, Michael, Garzorz-Stark, Natalie, Lauffer, Felix, Eyerich, Stefanie
Publikováno v:
In Journal of Investigative Dermatology August 2023 143(8):1461-1469
Autor:
Hardt, Michaela, Rajkomar, Alvin, Flores, Gerardo, Dai, Andrew, Howell, Michael, Corrado, Greg, Cui, Claire, Hardt, Moritz
Much work aims to explain a model's prediction on a static input. We consider explanations in a temporal setting where a stateful dynamical model produces a sequence of risk estimates given an input at each time step. When the estimated risk increase
Externí odkaz:
http://arxiv.org/abs/1907.04911
Autor:
Rajkomar, Alvin, Oren, Eyal, Chen, Kai, Dai, Andrew M., Hajaj, Nissan, Liu, Peter J., Liu, Xiaobing, Sun, Mimi, Sundberg, Patrik, Yee, Hector, Zhang, Kun, Duggan, Gavin E., Flores, Gerardo, Hardt, Michaela, Irvine, Jamie, Le, Quoc, Litsch, Kurt, Marcus, Jake, Mossin, Alexander, Tansuwan, Justin, Wang, De, Wexler, James, Wilson, Jimbo, Ludwig, Dana, Volchenboum, Samuel L., Chou, Katherine, Pearson, Michael, Madabushi, Srinivasan, Shah, Nigam H., Butte, Atul J., Howell, Michael, Cui, Claire, Corrado, Greg, Dean, Jeff
Publikováno v:
npj Digital Medicine 1:18 (2018)
Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variables from no
Externí odkaz:
http://arxiv.org/abs/1801.07860
Autor:
HOWELL, MICHAEL
Publikováno v:
Governance Directions. Dec2023, Vol. 75 Issue 11, p1178-1181. 4p.