# project_cptmem


## Effective Function-Space Regularization for Bayesian Neural Networks: Leverage the information from Learning Trajectory

This is an implemenation for "Compact Memory for Continual Logistic Regression"



## Description for implementation

* example_four_moons.ipynb : results for four-moon task

* setting_dataset.py                       : train R-FVI with informative priors for classification
* main_splitcifar100_basereplay_batch.py   : baseline experience replay for Split-CIFAR-100
* main_splitcifar100_baselambda_batch.py   : baseline K-prior  for Split-CIFAR-100
* main_splitcifar100_ourem_batch.py        : our method for Split-CIFAR-100 

* run_main_splitcifar100.sh                : execute experimentsr for Split-CIFAR-100  

