Search Results for author: Tom Huix

Found 5 papers, 2 papers with code

Central Limit Theorem for Bayesian Neural Network trained with Variational Inference

no code implementations10 Jun 2024 Arnaud Descours, Tom Huix, Arnaud Guillin, Manon Michel, Éric Moulines, Boris Nectoux

In this paper, we rigorously derive Central Limit Theorems (CLT) for Bayesian two-layerneural networks in the infinite-width limit and trained by variational inference on a regression task.

Variational Inference

Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians

no code implementations6 Jun 2024 Tom Huix, Anna Korba, Alain Durmus, Eric Moulines

In this view, VI over this specific family can be casted as the minimization of a Mollified relative entropy, i. e. the KL between the convolution (with respect to a Gaussian kernel) of an atomic measure supported on Diracs, and the target distribution.

Bayesian Inference LEMMA +1

VITS : Variational Inference Thompson Sampling for contextual bandits

1 code implementation19 Jul 2023 Pierre Clavier, Tom Huix, Alain Durmus

In this paper, we introduce and analyze a variant of the Thompson sampling (TS) algorithm for contextual bandits.

Thompson Sampling Variational Inference

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

no code implementations10 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

Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study

1 code implementation8 Jul 2022 Tom Huix, Szymon Majewski, Alain Durmus, Eric Moulines, Anna Korba

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.

Variational Inference

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