Luis A. Ortega

According to our database, Luis A. Ortega authored at least 14 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2026

Improving the Linearized Laplace Approximation via Quadratic Approximations.

Pedro Jiménez, Luis A. Ortega, Pablo Morales-Álvarez, Daniel Hernández-Lobato

CoRR, February, 2026

A large deviation theory analysis on the implicit bias of SGD.

Luis A. Ortega, Andrés R. Masegosa

Neurocomputing, 2026

Scalable Linearized Laplace Approximation via Surrogate Neural Kernel.

Luis A. Ortega, Simón Rodríguez Santana, Daniel Hernández-Lobato

Proceedings of the 34th European Symposium on Artificial Neural Networks, 2026

Improving the Linearized Laplace Approximation via Quadratic Approximations.

Pedro Jiménez García-Ligero, Luis A. Ortega, Pablo Morales-Álvarez, Daniel Hernández-Lobato

Proceedings of the 34th European Symposium on Artificial Neural Networks, 2026

2025

PAC-Chernoff Bounds: Understanding Generalization in the Interpolation Regime.

Andrés R. Masegosa, Luis A. Ortega

J. Artif. Intell. Res., 2025

2024

The Cold Posterior Effect Indicates Underfitting, and Cold Posteriors Represent a Fully Bayesian Method to Mitigate It.

Yijie Zhang, Yi-Shan Wu, Luis A. Ortega, Andrés R. Masegosa

Trans. Mach. Learn. Res., 2024

Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning.

Luis A. Ortega, Simón Rodríguez Santana, Daniel Hernández-Lobato

CoRR, 2024

PAC-Bayes-Chernoff bounds for unbounded losses.

Ioar Casado, Luis A. Ortega Andrés, Aritz Pérez, Andrés R. Masegosa

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Variational Linearized Laplace Approximation for Bayesian Deep Learning.

Luis A. Ortega Andrés, Simón Rodríguez Santana, Daniel Hernández-Lobato

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

If there is no underfitting, there is no Cold Posterior Effect.

Yijie Zhang, Yi-Shan Wu, Luis A. Ortega, Andrés R. Masegosa

CoRR, 2023

Understanding Generalization in the Interpolation Regime using the Rate Function.

Andrés R. Masegosa, Luis A. Ortega

CoRR, 2023

Deep Variational Implicit Processes.

Luis A. Ortega, Simón Rodríguez Santana, Daniel Hernández-Lobato

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Correcting Model Bias with Sparse Implicit Processes.

Simón Rodríguez Santana, Luis A. Ortega Andrés, Daniel Hernández-Lobato, Bryan Zaldivar

CoRR, 2022

Diversity and Generalization in Neural Network Ensembles.

Luis A. Ortega, Rafael Cabañas, Andrés R. Masegosa

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022