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.

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Causal Inference 396 61.11%
Decision Making 29 4.48%
Causal Discovery 26 4.01%
Time Series 26 4.01%
Fairness 19 2.93%
Recommendation Systems 13 2.01%
Selection bias 12 1.85%
Causal Identification 8 1.23%
General Classification 6 0.93%

Components


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

Categories