Skip to content

Latest commit

 

History

History
15 lines (11 loc) · 733 Bytes

README.md

File metadata and controls

15 lines (11 loc) · 733 Bytes

DOI

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