all AI news
A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts. (arXiv:2204.02028v2 [physics.ao-ph] UPDATED)
July 29, 2022, 1:10 a.m. | Lucy Harris, Andrew T. T. McRae, Matthew Chantry, Peter D. Dueben, Tim N. Palmer
cs.LG updates on arXiv.org arxiv.org
Despite continuous improvements, precipitation forecasts are still not as
accurate and reliable as those of other meteorological variables. A major
contributing factor to this is that several key processes affecting
precipitation distribution and intensity occur below the resolved scale of
global weather models. Generative adversarial networks (GANs) have been
demonstrated by the computer vision community to be successful at
super-resolution problems, i.e., learning to add fine-scale structure to coarse
images. Leinonen et al. (2020) previously applied a GAN to produce …
arxiv deep learning learning physics precipitation stochastic
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Senior Data Engineer
@ Displate | Warsaw
Professor/Associate Professor of Health Informatics [LKCMedicine]
@ Nanyang Technological University | NTU Novena Campus, Singapore
Research Fellow (Computer Science (and Engineering)/Electronic Engineering/Applied Mathematics/Perception Sciences)
@ Nanyang Technological University | NTU Main Campus, Singapore
Java Developer - Assistant Manager
@ State Street | Bengaluru, India
Senior Java/Python Developer
@ General Motors | Austin IT Innovation Center North - Austin IT Innovation Center North
Research Associate (Computer Engineering/Computer Science/Electronics Engineering)
@ Nanyang Technological University | NTU Main Campus, Singapore