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stat.ML2026
Improving the Linearized Laplace Approximation via Quadratic Approximations
Pedro Jiménez, Luis A. Ortega, Pablo Morales-Ãlvarez +1
Deep neural networks (DNNs) often produce overconfident out-of-distribution predictions, motivating Bayesian uncertainty quantification. The Linearized Laplace Approximation (LLA)…
stat.ML2024
PAC-Bayes-Chernoff bounds for unbounded losses
Ioar Casado, Luis A. Ortega, Aritz Pérez +1
We introduce a new PAC-Bayes oracle bound for unbounded losses that extends Cramér-Chernoff bounds to the PAC-Bayesian setting. The proof technique relies on controlling the tails…
stat.ML2024
Variational Linearized Laplace Approximation for Bayesian Deep Learning
Luis A. Ortega, Simón RodrÃguez 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…