Repository for paper, "Deep Extreme Mixture Model for Time series forecasting"
This provides implementation of VD-AE classifier model and forecaster modules
VD-AE classifier is the extension of work titled "Variational Disentanglement for Rare Event Modeling". GPD prior is extended for left extremes. The complete implemetation is given in VD_AE_classifer folder
training the classifier model can be done by executing
python train_VIE_multi_simulationDL_cv.py
Anomaly detection results are saved in same folder
Forecaster modules training and inference implementaion is given in extreme_gpd folder
extreme_gpd_3cls.ipynb invokes training function and infers predicton of unseen data
- install pytorch (you can follow instructions from here
- pip install -r requirements.txt
- Change parameters according to your data in train_VIE_multi_simulationDL_cv.py file
- Get classification results and use that for forecasting module
Requirements file can be installed using conda environemnt by following instructions from here or using docker as given here