- The codebase is mostly built upon MTT: https://github.com/GeorgeCazenavette/mtt-distillation
- Create a new conda environment by using requirements.txt file
- 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
- Save the buffer files in a directory and use the path of this directory in distill.py file.
- Run the bash file 'run_distill.sh' with the desired dataset and hyper-parameter to perform experiments.
-
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Repository containing codebase for work titled "Bayesian Pseudo-Coreset via Contrastive Divergence"
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backpropagator/BPC-CD
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