Stochastic weight averaging–Gaussian (SWAG)
Stochastic weight averaging–Gaussian (SWAG) is a technique in machine learning that improves model generalization and uncertainty estimation by approximating the posterior distribution of neural network weights using Gaussian distributions derived from stochastic weight averaging. It enhances predictive performance and reliability in deep learning models.