2 papers
stat.ML2025
Adaptive Variational Inference in Probabilistic Graphical Models: Beyond Bethe, Tree-Reweighted, and Convex Free Energies
Harald Leisenberger, Franz Pernkopf
Variational inference in probabilistic graphical models aims to approximate fundamental quantities such as marginal distributions and the partition function. Popular approaches are…
stat.ML2024
On the Convexity and Reliability of the Bethe Free Energy Approximation
Harald Leisenberger, Christian Knoll, Franz Pernkopf
The Bethe free energy approximation provides an effective way for relaxing NP-hard problems of probabilistic inference. However, its accuracy depends on the model parameters and pa…