Search Results for author:
Found 3 papers, 1 papers with code
VITS : Variational Inference Thomson Sampling for contextual bandits
In this paper, we introduce and analyze a variant of the Thompson sampling (TS) algorithm for contextual bandits.
Law of Large Numbers for Bayesian two-layer Neural Network trained with Variational Inference
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 of overparameterized Bayesian Neural Networks: a theoretical and empirical study
This paper studies the Variational Inference (VI) used for training Bayesian Neural Networks (BNN) in the overparameterized regime, i. e., when the number of neurons tends to infinity.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
