RolnickLab/constrained-downscaling
A project on how to incorporate physics constraints into deep learning architectures for downscaling or other super--resolution tasks.
Python
Stargazers
- AndreCNFLoka
- cbueloUS EPA
- chadagreeneNASA: Jet Propulsion Laboratory
- cheginitPurdue University
- chwing00
- diadestinyUESTC
- Ethan-yxx
- fernando-aristizabalERT
- fservaSouthern Europe
- gewitterblitzTexas A&M University
- haroro-star
- huangzq681Sun Yat-sen University
- HurriCaneBQLXinjiang University
- itsgifnotjiffMontreal
- jejjohnsonCSIC-UCM-IGEO
- jstaLos Alamos National Laboratory
- justinmillarPATH
- karoscXylem
- marvingabler@juaAI
- mdsumnerIntegrated Digital East Antarctica, Australian Antarctic Division
- NinaEffenbergerTübingen, Germany
- nshidqiCS KAIST & IBS Data Science Group
- onnyyonn
- pankajkarmanKIT Germany
- Paul-Aime
- paulaharderMila Quebec AI Institute
- pkopparla
- ransbymich@groq
- ringsaturn@caiyunapp
- santiagomotaFreelance
- seymakca
- timcdlucastimcdlucas.github.io
- timcera
- WyyyyyL
- xuejingkai
- YangZY2020