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Disambiguation of "Arrieta, Alejandro Barredo"

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Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI.

, , , , , , , , , , , and . CoRR, (2019)

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Katrin Arrieta

Alfonsina Aburto Arrieta

Ronald Arrieta Calvo

Alejandro Alfaro

In situ hybridization of the feline major satellite DNA FA-SAT in feline fibrosarcoma cell lines and feline fibrosarcoma tissue sections. Uni Gießen, (2009)

Antonio Arrieta Clavijo

 

Other publications of authors with the same name

Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI, , , , , , , , , and 2 other author(s). (2019)cite arxiv:1910.10045Comment: 67 pages, 13 figures, accepted for its publication in Information Fusion.Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI, , , , , , , , , and 2 other author(s). Information Fusion, (2020)Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI., , , , , , , , , and 2 other author(s). Inf. Fusion, (2020)On the post-hoc explainability of deep echo state networks for time series forecasting, image and video classification., , , , and . Neural Comput. Appl., 34 (13): 10257-10277 (2022)On generating trustworthy counterfactual explanations., , , , , and . Inf. Sci., (January 2024)Exploring the Trade-off between Plausibility, Change Intensity and Adversarial Power in Counterfactual Explanations using Multi-objective Optimization., , , , and . CoRR, (2022)Plausible Counterfactuals: Auditing Deep Learning Classifiers with Realistic Adversarial Examples., and . IJCNN, page 1-7. IEEE, (2020)On the Post-hoc Explainability of Deep Echo State Networks for Time Series Forecasting, Image and Video Classification., , , , and . CoRR, (2021)Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI., , , , , , , , , and 2 other author(s). CoRR, (2019)What Lies Beneath: A Note on the Explainability of Black-box Machine Learning Models for Road Traffic Forecasting., , and . ITSC, page 2232-2237. IEEE, (2019)