Interactive Streamlit app that runs over 15 causal discovery algorithms with method recommendation and bootstrap confidence graphs.
-
Updated
Nov 21, 2025 - Python
Interactive Streamlit app that runs over 15 causal discovery algorithms with method recommendation and bootstrap confidence graphs.
Auditing continuous-optimization DAG learners (NOTEARS, DAGMA): when high benchmark scores are really varsortability, what survives standardization, and a directed↔undirected bridge on real protein-signaling data.
🧠 Run over 15 causal discovery algorithms locally with Causal App, an easy-to-use tool built on Streamlit for effective causal analysis.
Add a description, image, and links to the notears topic page so that developers can more easily learn about it.
To associate your repository with the notears topic, visit your repo's landing page and select "manage topics."