Abstract
We study a message passing approach to power expectation propagation
for Bayesian model fitting and inference. Power expectation propagation is a class
of variational approximations based on the notion of α-divergence that extends two
notable approximations, namely mean field variational Bayes and expectation propagation. An illustration on a simple model allows to grasp benefits and complexities
of this methodology and sets the basis for applications on more complex models.
for Bayesian model fitting and inference. Power expectation propagation is a class
of variational approximations based on the notion of α-divergence that extends two
notable approximations, namely mean field variational Bayes and expectation propagation. An illustration on a simple model allows to grasp benefits and complexities
of this methodology and sets the basis for applications on more complex models.
| Original language | English |
|---|---|
| Title of host publication | Book of Short Papers SIS 2021 |
| Pages | 1026-1031 |
| Number of pages | 6 |
| ISBN (Electronic) | 9788891927361 |
| Publication status | Published - 2021 |