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Natalia Díaz-Rodríguez, PhD
Natalia Díaz-Rodríguez, PhD
Assistant Professor, University of Granada, Spain, DaSCI Andalusian Institute on Data Science
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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
41852020
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
3112020
State representation learning for control: An overview
T Lesort, N Díaz-Rodríguez, JF Goudou, D Filliat
Neural Networks 108, 379-392, 2018
2852018
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
2272014
Explainability in Deep Reinforcement Learning
A Heuillet, F Couthouis, N Díaz-Rodríguez
Knowledge-Based Systems 214, 106685, 2021
1712021
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
1372014
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
1142018
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
892021
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 Reinforcement Learning. arXiv preprint …, 2019
70*2019
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
692021
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
622018
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
52*2019
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
522019
Towards Explainable Neural-Symbolic Visual Reasoning
A Bennetot, JL Laurent, R Chatila, N Díaz-Rodríguez
NeSy workshop, IJCAI, Macao, Hong Kong, 2019, 2019
462019
A semantic security framework and context-aware role-based access control ontology for smart spaces
S Hosseinzadeh, S Virtanen, N Díaz-Rodríguez, J Lilius
Proceedings of the International Workshop on Semantic Big Data, 1-6, 2016
462016
Physical activity among children: objective measurements using Fitbit One® and ActiGraph
L Hamari, T Kullberg, J Ruohonen, OJ Heinonen, N Díaz-Rodríguez, ...
BMC Research Notes 10 (1), 161, 2017
452017
A framework for context-aware applications for smart spaces
MM Saleemi, ND Rodríguez, J Lilius, I Porres
Smart Spaces and Next Generation Wired/Wireless Networking, 14-25, 2011
452011
Validation Techniques for Sensor Data in Mobile Health Applications
IM Pires, NM Garcia, N Pombo, F Flórez-Revuelta, N Díaz-Rodríguez
Journal of Sensors 2016, 1-9, 2016
442016
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
382021
S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning
A Raffin, A Hill, R Traoré, T Lesort, N Díaz-Rodríguez, D Filliat
NeurIPS workshop on Deep Reinforcement Learning, 2018
352018
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Artikelen 1–20