Skip to content

Parametric generation of conditional geological realizations using generative neural networks

Notifications You must be signed in to change notification settings

chanshing/geocondition

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Parametric generation of conditional geological realizations using generative neural networks (arXiv)

Requires PyTorch 0.4+

Run with python main.py [--options]

  • Z

  • X

  • O

You can download our pre-trained unconditional generator netG.pth here (12MB), which has been trained using Wasserstein GAN (https://arxiv.org/abs/1701.07875)

  • main.py main code
  • models.py neural network architectures
  • utils.py helper functions
  • dat/cond*.dat conditioning test cases

About

Parametric generation of conditional geological realizations using generative neural networks

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Languages