UCLA-SETI-Group / doom

A Machine Learning Based Direction-of-origin Filter for the Excision of Radio Frequency Interference in the Search for Technosignatures

doom

A Machine-Learning-Based Direction-of-Origin Filter for the Identification of Radio Frequency Interference in the Search for Technosignatures

demo.ipynb

In this notebook, we provide the code to replicate the results presented by Pinchuk & Margot (2021). Before continuing, make sure you download the test data and final model weights and unzip them in the main directory of the repository.

The implementation details are spread over four main files:

• models.py
• model_utils.py
• data_utils.py
• utils.py