AI-ordlista
Den kompletta ordlistan över AI
Réseaux Bayésiens
Modèles graphiques probabilistes représentant les variables aléatoires et leurs dépendances conditionnelles par un graphe orienté acyclique.
Méthodes MCMC
Algorithmes de Monte Carlo par Chaîne de Markov pour échantillonner des distributions de probabilité complexes et calculer des approximations bayésiennes.
Inférence Variationnelle
Technique d'optimisation transformant les problèmes d'inférence bayésienne en problèmes d'optimisation par approximation variationnelle.
Bayesian Filtering
Sequential methods for estimating the state of a dynamic system by progressively incorporating new observations.
Bayesian Hypothesis Testing
Alternative approaches to classical tests using posterior probabilities to evaluate statistical hypotheses.
Bayesian Hierarchical Models
Multi-level structures where parameters of one level become data for the upper level, allowing information sharing.
Bayesian Model Selection
Methods for comparing and selecting statistical models using Bayes factors or posterior information.
Gaussian Processes
Powerful tools for Bayesian regression and classification, modeling functions as distributions over function spaces.
Empirical Bayes
Approach where prior hyperparameters are estimated from data rather than specified subjectively.
Bayesian Causal Inference
Application of Bayesian methods to identify and quantify causal relationships between variables from observational data.
Probabilistic Programming
Programming paradigm that integrates probabilistic primitives to specify and automatically solve Bayesian inference problems.
Approximate Inference
Set of techniques for computing efficient approximations when exact Bayesian inference is computationally impossible.