Juan Maroñas Molano

Francisco Javier Sáez-Maldonado

Neural Comput. Appl., May, 2024

2023

Deep Transformed Gaussian Processes.

[BibT_eX]

[DOI]

Daniel Hernández-Lobato

CoRR, 2023

Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models.

[BibT_eX]

[DOI]

CoRR, 2023

Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification.

[BibT_eX]

[DOI]

Daniel Hernández-Lobato

Proceedings of the International Conference on Machine Learning, 2023

2021

A deep analysis on high-resolution dermoscopic image classification.

[BibT_eX]

[DOI]

IET Comput. Vis., 2021

Transforming Gaussian Processes With Normalizing Flows.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Calibration of deep probabilistic models with decoupled bayesian neural networks.

[BibT_eX]

[DOI]

Neurocomputing, 2020

Improving Calibration in Mixup-trained Deep Neural Networks through Confidence-Based Loss Functions.

[BibT_eX]

[DOI]

CoRR, 2020

On Calibration of Mixup Training for Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2020

Confidence Calibration for Deep Renal Biopsy Immunofluorescence Image Classification.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019

Bayesian Strategies for Likelihood Ratio Computation in Forensic Voice Comparison with Automatic Systems.

[BibT_eX]

[DOI]

Alicia Lozano-Diez

CoRR, 2019

2018

Generative Models for Deep Learning with Very Scarce Data.

[BibT_eX]

[DOI]

Juan Maroñas Molano