Tag: possibilistic

Maxitive Donsker-Varadhan Formulation for Possibilistic Variational Inference arXiv:2511.21223v1 Announce Type: new Abstract: Variational inference (VI) is a cornerstone of modern Bayesian learning, enabling approximate inference in complex models that would otherwise be intractable. However, its formulation depends on expectations and divergences defined through high-dimensional integrals, often rendering analytical treatment impossible and necessitating heavy reliance on…