Diversity and Generalization in Neural Network Ensembles. - Luis A. Ortega 001; Rafael Cabañas 001; Andrés R. Masegosa (AISTATS, 2022)

Correcting Model Bias with Sparse Implicit Processes. - Simón Rodríguez Santana; Luis A. Ortega Andrés; Daniel Hernández-Lobato; Bryan Zaldivar (CoRR, 2022)

Deep Variational Implicit Processes. - Luis A. Ortega 001; Simón Rodríguez Santana; Daniel Hernández-Lobato (ICLR, 2023)

Understanding Generalization in the Interpolation Regime using the Rate Function. - Andrés R. Masegosa; Luis A. Ortega 001 (CoRR, 2023)

If there is no underfitting, there is no Cold Posterior Effect. - Yijie Zhang; Yi-Shan Wu 003; Luis A. Ortega 001; Andrés R. Masegosa (CoRR, 2023)

Variational Linearized Laplace Approximation for Bayesian Deep Learning. - Luis A. Ortega Andrés; Simón Rodríguez Santana; Daniel Hernández-Lobato (ICML, 2024)

PAC-Bayes-Chernoff bounds for unbounded losses. - Ioar Casado; Luis A. Ortega Andrés; Aritz Pérez; Andrés R. Masegosa (NeurIPS, 2024)

Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning. - Luis A. Ortega 001; Simón Rodríguez Santana; Daniel Hernández-Lobato (CoRR, 2024)

The Cold Posterior Effect Indicates Underfitting, and Cold Posteriors Represent a Fully Bayesian Method to Mitigate It. - Yijie Zhang; Yi-Shan Wu 003; Luis A. Ortega 001; Andrés R. Masegosa (Trans. Mach. Learn. Res., 2024)

PAC-Chernoff Bounds: Understanding Generalization in the Interpolation Regime. - Andrés R. Masegosa; Luis A. Ortega 001 (J. Artif. Intell. Res., 2025)