research
∙
06/07/2023
Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching
Quantification learning deals with the task of estimating the target lab...
share
research
∙
02/23/2023
Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes
Bernstein's condition is a key assumption that guarantees fast rates in ...
research
∙
02/23/2022
On PAC-Bayesian reconstruction guarantees for VAEs
Despite its wide use and empirical successes, the theoretical understand...
research
∙
10/01/2020
Estimation of copulas via Maximum Mean Discrepancy
This paper deals with robust inference for parametric copula models. Est...
research
∙
12/12/2019
Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence
Many works in statistics aim at designing a universal estimation procedu...
research
∙
09/29/2019
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy
In some misspecified settings, the posterior distribution in Bayesian st...
research
∙
08/09/2019
Generalization Error Bounds for Deep Variational Inference
Variational inference is becoming more and more popular for approximatin...
research
∙
08/09/2019
Convergence Rates of Variational Inference in Sparse Deep Learning
Variational inference is becoming more and more popular for approximatin...
research
∙
04/08/2019
A Generalization Bound for Online Variational Inference
Bayesian inference provides an attractive online-learning framework to a...
research
∙
10/28/2018
Consistency of ELBO maximization for model selection
The Evidence Lower Bound (ELBO) is a quantity that plays a key role in v...
research
∙
05/14/2018
