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math.PR2024
Large deviations of the empirical measures of a strong-Feller Markov process inside a subset and quasi-ergodic distribution
Arnaud Guillin, Boris Nectoux, Liming Wu
In this work, we establish, for a strong Feller process, the large deviation principle for the occupation measure conditioned not to exit a given subregion. The rate function vanis…
stat.ML2024
Central Limit Theorem for Bayesian Neural Network trained with Variational Inference
Arnaud Descours, Tom Huix, Arnaud Guillin +3
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 regress…