activity
20102024
most citedCombinatorial Optimization by Learning and Simulation of Bayesian Networks

116 citations · 267 across the 30 of their papers we have counts for

collaborators

33 papers

cs.NE2024★ 22 cited

Comparative study of regression vs pairwise models for surrogate-based heuristic optimisation

Pablo S. Naharro, Pablo Toharia, Antonio LaTorre +1

Heuristic optimisation algorithms explore the search space by sampling solutions, evaluating their fitness, and biasing the search in the direction of promising solutions. However,…

eess.IV2024★ 4 cited

3D Segmentation of Neuronal Nuclei and Cell-Type Identification using Multi-channel Information

Antonio LaTorre, Lidia Alonso-Nanclares, José María Peña +1

Background Analyzing images to accurately estimate the number of different cell types in the brain using automatic methods is a major objective in neuroscience. The automatic and s…

cs.NE2024★ 11 cited

Model calibration using a parallel differential evolution algorithm in computational neuroscience: simulation of stretch induced nerve deficit

Antonio LaTorre, Man Ting Kwong, Julián A. García-Grajales +3

Neuronal damage, in the form of both brain and spinal cord injuries, is one of the major causes of disability and death in young adults worldwide. One way to assess the direct dama…

stat.ME2023

Bounding the Probabilities of Benefit and Harm Through Sensitivity Parameters and Proxies

Jose M. Peña

We present two methods for bounding the probabilities of benefit and harm under unmeasured confounding. The first method computes the (upper or lower) bound of either probability a…

stat.ME2022★ 1 cited

-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows

Sourabh Balgi, Jose M. Peña, Adel Daoud

We propose a novel sensitivity analysis to unobserved confounding in observational studies using copulas and normalizing flows. Using the idea of interventional equivalence of stru…

cs.AI2022★ 3 cited

Counterfactual Analysis of the Impact of the IMF Program on Child Poverty in the Global-South Region using Causal-Graphical Normalizing Flows

Sourabh Balgi, Jose M. Peña, Adel Daoud

This work demonstrates the application of a particular branch of causal inference and deep learning models: \emph{causal-Graphical Normalizing Flows (c-GNFs)}. In a recent contribu…