Ernesto Curbelo

According to our database, Ernesto Curbelo authored at least 10 papers between 2021 and 2026.

Collaborative distances:

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

2026

An automatic counting algorithm for the quantification and uncertainty analysis of the number of microglial cells trainable in small and heterogeneous datasets.

Luca Martino, M. M. Garcia, P. S. Paradas, Ernesto Curbelo

Expert Syst. Appl., 2026

2025

Neural lasso: a unifying approach of lasso and neural networks.

Ernesto Curbelo, David Delgado-Gómez, Danae Carreras

Int. J. Data Sci. Anal., August, 2025

Enhancing Graphical Lasso: A Robust Scheme for Non-Stationary Mean Data.

Samuel Rey, Ernesto Curbelo, Luca Martino, Fernando Llorente, Antonio G. Marques

CoRR, March, 2025

Corrigendum to "pyLAIS: A Python package for Layered Adaptive Importance Sampling" [SoftwareX 29 (2025), 101976].

Ernesto Curbelo, Luca Martino, David Delgado-Gómez

SoftwareX, 2025

pyLAIS: A Python package for Layered Adaptive Importance Sampling.

Ernesto Curbelo, Luca Martino, David Delgado-Gómez

SoftwareX, 2025

Adaptive posterior distributions for uncertainty analysis of covariance matrices in Bayesian inversion problems for multioutput signals.

Ernesto Curbelo, Luca Martino, Fernando Llorente, David Delgado-Gómez

J. Frankl. Inst., 2025

2023

Neural lasso: a unifying approach of lasso and neural networks.

David Delgado, Ernesto Curbelo, Danae Carreras-García

CoRR, 2023

2022

Safe importance sampling based on partial posteriors and neural variational approximations.

Fernando Llorente, Ernesto Curbelo, Luca Martino, Pablo M. Olmos, David Delgado

Proceedings of the 30th European Signal Processing Conference, 2022

2021

Automatic tempered posterior distributions for Bayesian inversion problems.

Luca Martino, Fernando Llorente, Ernesto Curbelo, Javier López-Santiago, Joaquín Míguez

CoRR, 2021

MCMC-driven importance samplers.

Fernando Llorente, Ernesto Curbelo, Luca Martino, Victor Elvira, David Delgado

CoRR, 2021