Zobrazeno 1 - 10
of 120
pro vyhledávání: '"Hickey, Jason"'
Autor:
Sirko, Wojciech, Brempong, Emmanuel Asiedu, Marcos, Juliana T. C., Annkah, Abigail, Korme, Abel, Hassen, Mohammed Alewi, Sapkota, Krishna, Shekel, Tomer, Diack, Abdoulaye, Nevo, Sella, Hickey, Jason, Quinn, John
Mapping buildings and roads automatically with remote sensing typically requires high-resolution imagery, which is expensive to obtain and often sparsely available. In this work we demonstrate how multiple 10 m resolution Sentinel-2 images can be use
Externí odkaz:
http://arxiv.org/abs/2310.11622
Autor:
Agrawal, Shreya, Carver, Rob, Gazen, Cenk, Maddy, Eric, Krasnopolsky, Vladimir, Bromberg, Carla, Ontiveros, Zack, Russell, Tyler, Hickey, Jason, Boukabara, Sid
Post-processing typically takes the outputs of a Numerical Weather Prediction (NWP) model and applies linear statistical techniques to produce improve localized forecasts, by including additional observations, or determining systematic errors at a fi
Externí odkaz:
http://arxiv.org/abs/2303.16301
Publikováno v:
Artificial Intelligence for the Earth Systems (2023)
Heat waves are projected to increase in frequency and severity with global warming. Improved warning systems would help reduce the associated loss of lives, wildfires, power disruptions, and reduction in crop yields. In this work, we explore the pote
Externí odkaz:
http://arxiv.org/abs/2205.10972
Autor:
Espeholt, Lasse, Agrawal, Shreya, Sønderby, Casper, Kumar, Manoj, Heek, Jonathan, Bromberg, Carla, Gazen, Cenk, Hickey, Jason, Bell, Aaron, Kalchbrenner, Nal
The problem of forecasting weather has been scientifically studied for centuries due to its high impact on human lives, transportation, food production and energy management, among others. Current operational forecasting models are based on physics a
Externí odkaz:
http://arxiv.org/abs/2111.07470
Publikováno v:
In Canadian Journal of Diabetes March 2024 48(2):82-88
Autor:
Huot, Fantine, Hu, R. Lily, Ihme, Matthias, Wang, Qing, Burge, John, Lu, Tianjian, Hickey, Jason, Chen, Yi-Fan, Anderson, John
Identifying regions that have high likelihood for wildfires is a key component of land and forestry management and disaster preparedness. We create a data set by aggregating nearly a decade of remote-sensing data and historical fire records to predic
Externí odkaz:
http://arxiv.org/abs/2010.07445
Autor:
Sønderby, Casper Kaae, Espeholt, Lasse, Heek, Jonathan, Dehghani, Mostafa, Oliver, Avital, Salimans, Tim, Agrawal, Shreya, Hickey, Jason, Kalchbrenner, Nal
Weather forecasting is a long standing scientific challenge with direct social and economic impact. The task is suitable for deep neural networks due to vast amounts of continuously collected data and a rich spatial and temporal structure that presen
Externí odkaz:
http://arxiv.org/abs/2003.12140
High-resolution nowcasting is an essential tool needed for effective adaptation to climate change, particularly for extreme weather. As Deep Learning (DL) techniques have shown dramatic promise in many domains, including the geosciences, we present a
Externí odkaz:
http://arxiv.org/abs/1912.12132
A key challenge in metasurface design is the development of algorithms that can effectively and efficiently produce high performance devices. Design methods based on iterative optimization can push the performance limits of metasurfaces, but they req
Externí odkaz:
http://arxiv.org/abs/1811.12436
Publikováno v:
PNAS July 30, 2019 116 (31) 15344-15349
The numerical solution of partial differential equations (PDEs) is challenging because of the need to resolve spatiotemporal features over wide length and timescales. Often, it is computationally intractable to resolve the finest features in the solu
Externí odkaz:
http://arxiv.org/abs/1808.04930