AI-ordlista
Den kompletta ordlistan över AI
Causal Graphs
Graphical representation of cause-and-effect relationships between variables using DAGs and other structures.
Structural Causal Models
Mathematical formalism combining structural equations and graphs to model causal mechanisms.
Counterfactuals
Analysis of hypothetical scenarios to determine what would have happened under different conditions.
Causal Discovery
Automatic algorithms to identify causal relationships from observational data
Propensity Score
Statistical technique to reduce selection bias in non-randomized observational studies.
Instrumental Variables
Causal estimation method using variables correlated with the treatment but independent of the outcome.
Do-Calculus
Système formel de règles pour manipuler les expressions causales et identifier les effets estimables.
Causal Inference in Time Series
Application of causal methods to sequential data to identify temporal relationships.
Causal Mediation
Analysis of the intermediate mechanisms through which a cause affects its effect.
Robust Causal Inference
Methods resistant to hypothesis violations and noisy or incomplete data.
Causal Reinforcement Learning
Integrating causal principles into RL algorithms to improve generalization.
High-Dimensional Causal Inference
Techniques adapted to data with a large number of variables compared to observations.