SenseGen: A Deep Learning Architecture for Synthetic Sensor Data Generation

This is an implementation for the generative model used in SenseGen paper SenseGen: A Deep Learning Architecture for Synthetic Sensor Data Generation

Authors:

• Moustafa Alzantot (malzantot)
• Supriyo Charkaborty (supriyogit)
• Prof. Mani Srivastava

Usage

To be able to run the examples you need to download checkpoints for provided models as well as dataset.

To download the dataset and all checkpoints run following:

./download_dataset.sh

Then run and train the model by running the SenseGenModel.ipynb notebook.

All rights reserved Networked and Embedded Systems Lab (NESL), UCLA.