bayesian

Definition

Treating unknowns as probability distributions rather than single values: a prior is combined with observed data to yield a posterior. The payoff is calibrated uncertainty — the model reports not just an answer but how confident it should be — which matters for active learning, experimental design, and safety-critical decisions. Exact inference is usually intractable, so Bayesian methods in practice lean on variational approximations or sampling.

Explainers using this term

• Kernel Methods and Gaussian Processes — The Champions Before Neural NetsPractical Bayesian Optimization of Machine Learning Algorithms
• Time-Series Anomaly Detection — The Math Behind the AlertsBayesian Online Changepoint Detection
• Recommenders and Embeddings — Same Math as RAG, Different GoalBPR: Bayesian Personalized Ranking from Implicit Feedback