Causal inference

Causal inference is the process of drawing a conclusion about a causal connection based on the conditions of the occurrence of an effect. The main difference between causal inference and inference of association is that the former analyzes the response of the effect variable when the cause is changed.


Paper Code Results Date Stars


Task Papers Share
Causal Inference 439 53.67%
Causal Discovery 32 3.91%
Decision Making 27 3.30%
Time Series Analysis 26 3.18%
BIG-bench Machine Learning 22 2.69%
Fairness 19 2.32%
Test 19 2.32%
Selection bias 13 1.59%
Recommendation Systems 12 1.47%


Component Type
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