invariantmass - Initial Release: InvariantMass v1.0.0

This is the first official release of InvariantMass, a project for predicting the dielectron invariant mass using multiple machine learning approaches. It includes:

🔬 Key Features

• Data Processing & Encoding:
  
  • Scripts to normalize tabular HEP data
    
  • Hadronic image encoding in 3-channel and 40×40×1 formats
    
• Model Implementations:
  
  • Deep Neural Network (DNN) on tabular data
    
  • Convolutional Neural Network (CNN) on image representations
    
  • Boosted Decision Tree (BDT) comparisons
    
• Notebooks & Results:
  
  • Jupyter notebooks for training, evaluation, and visualization
    
  • MAE, R², and distribution-overlap analyses
    
  • Generated plots in /images for direct inspection
    
• Citation Metadata:
  
  • CITATION.cff for automated GitHub & Zenodo citation
    
• Documentation:
  
  • Updated README.md with overview, usage, and contribution guidelines
    
• License: MIT

This release is configured for Zenodo archiving and will be assigned a DOI for citation.

- Jupyter Notebook
Published by HaiderPhys21 9 months ago