4 citations · 7 across the 11 of their papers we have counts for
3 papers · 1 filter
If there is no underfitting, there is no Cold Posterior Effect
Yijie Zhang, Yi-Shan Wu, Luis A. Ortega +1
The cold posterior effect (CPE) (Wenzel et al., 2020) in Bayesian deep learning shows that, for posteriors with a temperature , the resulting posterior predictive could have b…
PAC-Chernoff Bounds: Understanding Generalization in the Interpolation Regime
Andrés R. Masegosa, Luis A. Ortega
This paper introduces a distribution-dependent PAC-Chernoff bound that exhibits perfect tightness for interpolators, even within over-parameterized model classes. This bound, which…
Variational Linearized Laplace Approximation for Bayesian Deep Learning
Luis A. Ortega, Simón Rodríguez Santana, Daniel Hernández-Lobato
The Linearized Laplace Approximation (LLA) has been recently used to perform uncertainty estimation on the predictions of pre-trained deep neural networks (DNNs). However, its wide…