Anomaly Detection Using Contrastive Learning (Electron-Photon)
Overview:
This project aims to detect Electrons (Anomaly) by training the model only on the Photons using Contrastive Learning.
Dataset:
For the top quark dataset:
https://drive.google.com/drive/folders/1WXc1-wetvaiufNzAcVg23DEBK2QBYhp9?usp=sharing
And the Electron-Photon dataset can be downloaded from these links:
https://cernbox.cern.ch/index.php/s/sHjzCNFTFxutYCj/download
https://cernbox.cern.ch/index.php/s/69nGEZjOy3xGxBq/download
Requirements:
Strong knowledge of Python; Keras.
No need for a strong math background.
Note:
The code is still under verification.
This project was mentored by Prof. Sergei V. Gleyzer and Ali Hariri.