Recurrent U-net: Deep learning to predict summertime ozone over the United States
- ADS bibcode
- 2019AGUFM.A51U2676H
- year
- 2019
- Listed Authors
- He, T. L.
- Huang, B.
- Liu, Y.
- Jones, D. B. A.
- Miyazaki, K.
- Jiang, Z.
- White, E. C.
- Worden, H. M.
- Worden, J.
- Listed Institutions
- Department of Physics, University of Toronto, Toronto, ON, Canada
- School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, United States
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Department of Physics, University of Toronto, Toronto, ON, Canada
- NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
- University of Science and Technology of China, Hefei, China
- Department of Physics, University of Toronto, Toronto, ON, Canada
- Atmospheric Chemistry Observations & Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO, United States
- California Institute of Technology, Jet Propulsion Laboratory, Pasadena, CA, United States
Linked Authors [?]
Linked Institutions