Skip to content

padmaksha18/DRMDIT-AE

Repository files navigation

DLSCA-AE

  • The model is coded in "AE.py"
  • Run it as below. Choose the hyperparams accordingly.
  • python3 AE.py --code_size 9 --w_reg 0.001 --a_reg 0.2 --num_epochs 25 --max_gradient_norm 0.5 --learning_rate 0.001 --hidden_size 64
  • TS_datasets.py has the file location for the train and test data. The DATA folder has the normal and anomaly files. The details and results can be found in the paper.

About

Deep info-theory learning kernel autoencoders

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published