Law of Large Numbers for Bayesian two-layer Neural Network trained with Variational Inference

no code implementations • 10 Jul 2023 • Arnaud Descours, Tom Huix, Arnaud Guillin, Manon Michel, Éric Moulines, Boris Nectoux

We provide a rigorous analysis of training by variational inference (VI) of Bayesian neural networks in the two-layer and infinite-width case.

Variational Inference

Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity

no code implementations • 3 Feb 2023 • Vincent Souveton, Arnaud Guillin, Jens Jasche, Guilhem Lavaux, Manon Michel

Normalizing Flows (NF) are Generative models which are particularly robust and allow for exact sampling of the learned distribution.

Bayesian Inference