activity
20182023
most citedExplainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

39 citations · 202 across the 12 of their papers we have counts for

collaborators

21 papers

cs.CY202335 cited

Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation

Natalia Díaz-Rodríguez, Javier Del Ser, Mark Coeckelbergh +3

Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system's entire life cycle: it…

cs.CV20222 cited

Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classification

Adrien Bennetot, Gianni Franchi, Javier Del Ser +2

Although Deep Neural Networks (DNNs) have great generalization and prediction capabilities, their functioning does not allow a detailed explanation of their behavior. Opaque deep l…

cs.LG20224 cited

Exploring the Trade-off between Plausibility, Change Intensity and Adversarial Power in Counterfactual Explanations using Multi-objective Optimization

Javier Del Ser, Alejandro Barredo-Arrieta, Natalia Díaz-Rodríguez +2

There is a broad consensus on the importance of deep learning models in tasks involving complex data. Often, an adequate understanding of these models is required when focusing on…

cs.AI20211 cited

Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley Values

Alexandre Heuillet, Fabien Couthouis, Natalia Díaz-Rodríguez

While Explainable Artificial Intelligence (XAI) is increasingly expanding more areas of application, little has been applied to make deep Reinforcement Learning (RL) more comprehen…

cs.CY2021

Questioning causality on sex, gender and COVID-19, and identifying bias in large-scale data-driven analyses: the Bias Priority Recommendations and Bias Catalog for Pandemics

Natalia Díaz-Rodríguez, Rūta Binkytė-Sadauskienė, Wafae Bakkali +4

The COVID-19 pandemic has spurred a large amount of observational studies reporting linkages between the risk of developing severe COVID-19 or dying from it, and sex and gender. By…

cs.LG20212 cited

Explaining Credit Risk Scoring through Feature Contribution Alignment with Expert Risk Analysts

Ayoub El Qadi, Natalia Diaz-Rodriguez, Maria Trocan +1

Credit assessments activities are essential for financial institutions and allow the global economy to grow. Building robust, solid and accurate models that estimate the probabilit…