Thuật ngữ AI
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Modèles Causaux Structurels (SCM)
Formalisation mathématique des relations de cause à effet utilisant des équations structurelles et des variables latentes.
Graphes Acycliques Dirigés (DAG)
Représentation visuelle des dépendances causales entre variables sans cycles directionnels.
Do-Calculus de Pearl
Ensemble de règles formelles pour manipuler les expressions causales et calculer les effets des interventions.
Counterfactual Causal Inference
Analysis of hypothetical scenarios to estimate what would have happened if a different cause had occurred.
Propensity Score
Technique for estimating the probability of treatment and reducing selection bias in observational studies.
Instrumental Variables
Method using external variables to identify causal effects in the presence of unobserved confounding variables.
Causal Mediation
Analysis of the intermediate mechanisms through which a cause produces its effect on an outcome variable.
Causalité en Séries Temporelles
Détection et analyse des relations de cause à effet dans les données séquentielles temporelles.
Causal Inference in High Dimension
Adapted techniques to identify causal relationships with a large number of variables compared to observations.
Natural and Quasi-Experimental Experiences
Methods exploiting exogenous events or natural variations to estimate causal effects.
Causal Reinforcement Learning
Integration of causal principles in reinforcement learning algorithms to improve generalization.
Causal Discovery
Algorithms for automatically discovering the underlying causal structure from observational data.