py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 49%Quantifying drivers of photovoltaic power generation at Bhadla using explainable machine learning and causal discovery - Nature →
- PossiblePossibly related (embedding) · 48%Anti-Causal Domain Generalization: Leveraging Unlabeled Data - Apple Machine Learning Research →
- PossiblePossibly related (embedding) · 51%Relaxing Faithfulness with Intervention-Only Causal Discovery →
- PossiblePossibly related (embedding) · 52%Amir combines economics and machine learning - vijesti.me →