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Welcome to reproscreener's documentation!

reproscreener aims to address challenges in robustness, transparency, and interpretability of ML models by automating verification of machine learning models at scale 1.

Note

This project is under active development.

  1. Bhaskar, A. and Stodden, V. 2024. Reproscreener: Leveraging LLMs for Assessing Computational Reproducibility of Machine Learning Pipelines. Proceedings of the 2nd ACM Conference on Reproducibility and Replicability (New York, NY, USA, Jul. 2024), 101--109. ↩