Skip to content

Repository containing codebase for work titled "Bayesian Pseudo-Coreset via Contrastive Divergence"

License

Notifications You must be signed in to change notification settings

backpropagator/BPC-CD

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

  1. The codebase is mostly built upon MTT: https://github.com/GeorgeCazenavette/mtt-distillation
  2. Create a new conda environment by using requirements.txt file
  3. You need to create a buffer file that should contain the training trajectories. To do this, we refer you to instructions provided in MTT: https://github.com/GeorgeCazenavette/mtt-distillation
  4. Save the buffer files in a directory and use the path of this directory in distill.py file.
  5. Run the bash file 'run_distill.sh' with the desired dataset and hyper-parameter to perform experiments.

About

Repository containing codebase for work titled "Bayesian Pseudo-Coreset via Contrastive Divergence"

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published