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Natalia Díaz-Rodríguez, PhD (ORCID: 0000-0003-3362-9326)
Natalia Díaz-Rodríguez, PhD (ORCID: 0000-0003-3362-9326)
Professor, University of Granada, Spain, DaSCI Andalusian Institute on Data Science (RoR:04njjy449)
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Zitiert von
Zitiert von
Jahr
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
AB Arrieta, N Díaz-Rodríguez, J Del Ser, A Bennetot, S Tabik, A Barbado, ...
Information Fusion 58, 82-115, 2020
79912020
Continual Learning for Robotics: Definition, Framework, Learning Strategies, Opportunities and Challenges
T Lesort, V Lomonaco, A Stoian, D Maltoni, D Filliat, N Díaz-Rodríguez
Information Fusion, 2020
5372020
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
S Ali, T Abuhmed, S El-Sappagh, K Muhammad, JM Alonso-Moral, ...
Information Fusion 99, 101805, 2023
4932023
State representation learning for control: An overview
T Lesort, N Díaz-Rodríguez, JF Goudou, D Filliat
Neural Networks 108, 379-392, 2018
3862018
Explainability in Deep Reinforcement Learning
A Heuillet, F Couthouis, N Díaz-Rodríguez
Knowledge-Based Systems 214, 106685, 2021
3582021
A survey on ontologies for human behavior recognition
ND Rodríguez, MP Cuéllar, J Lilius, MD Calvo-Flores
ACM Computing Surveys (CSUR) 46 (4), 1-33, 2014
2372014
Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation
N Díaz-Rodríguez, J Del Ser, M Coeckelbergh, ML de Prado, ...
Information Fusion 99, 101896, 2023
2322023
Explainable Artificial Intelligence (XAI) on Time Series Data: A Survey
T Rojat, R Puget, D Filliat, J Del Ser, R Gelin, N Díaz-Rodríguez
arXiv preprint arXiv:2104.00950, 2021
2012021
Don't forget, there is more than forgetting: new metrics for Continual Learning
N Díaz-Rodríguez, V Lomonaco, D Filliat, D Maltoni
NeurIPS workshop on Continual Learning 2018, 2018
1902018
Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence
A Holzinger, M Dehmer, F Emmert-Streib, R Cucchiara, I Augenstein, ...
Information Fusion, 2021
1812021
A fuzzy ontology for semantic modelling and recognition of human behaviour
ND Rodríguez, MP Cuéllar, J Lilius, MD Calvo-Flores
Knowledge-Based Systems 66, 46-60, 2014
1602014
Human-Centered Artificial Intelligence for Designing Accessible Cultural Heritage
G Pisoni, N Díaz-Rodríguez, H Gijlers, L Tonolli
Applied Sciences 11 (2), 870, 2021
1132021
DisCoRL: Continual Reinforcement Learning via Policy Distillation
R Traoré, H Caselles-Dupré, T Lesort, T Sun, G Cai, N Díaz-Rodríguez, ...
ICML 2019 Workshop on Multi-task and Lifelong Reinforcement Learning, Long …, 2019
107*2019
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case
N Díaz-Rodríguez, A Lamas, J Sanchez, G Franchi, I Donadello, S Tabik, ...
Information Fusion 79, 58-83, 2021
852021
Open-ended learning: a conceptual framework based on representational redescription
S Doncieux, D Filliat, N Díaz-Rodríguez, T Hospedales, R Duro, A Coninx, ...
Frontiers in neurorobotics 12, 59, 2018
752018
Towards Explainable Neural-Symbolic Visual Reasoning
A Bennetot, JL Laurent, R Chatila, N Díaz-Rodríguez
NeSy workshop, IJCAI, Macao, Hong Kong, 2019, 2019
742019
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities
R Kusters, D Misevic, H Berry, A Cully, Y Le Cunff, L Dandoy, ...
Frontiers in Big Data 3, 45, 2020
712020
Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics
A Raffin, A Hill, R Traoré, T Lesort, N Díaz-Rodríguez, D Filliat
ICLR 2019 Workshop on Structure & Priors in Reinforcement Learning (SPIRL …, 2019
642019
Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley Values
A Heuillet, F Couthouis, N Díaz-Rodríguez
IEEE Computational Intelligence Magazine (Also in arXiv preprint arXiv …, 2022
602022
Deep unsupervised state representation learning with robotic priors: a robustness analysis
T Lesort, M Seurin, X Li, N Díaz-Rodríguez, D Filliat
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
59*2019
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