Symmetry Guarantees Statistic Recovery in Variational Inference

ArXi:2604.18310v1 Announce Type: cross Variational inference (VI) is a central tool in modern machine learning, used to approximate an intractable target density by optimising over a tractable family of distributions. As the variational family cannot typically represent the target exactly, guarantees on the quality of the resulting approximation are crucial for understanding which of its properties VI can faithfully capture.