Natalia Díaz Rodríguez

Orcid: 0000-0003-3362-9326

According to our database1, Natalia Díaz Rodríguez authored at least 71 papers between 2011 and 2025.

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Bibliography

2025
A Practical Tutorial on Explainable AI Techniques.
ACM Comput. Surv., February, 2025

2024
On generating trustworthy counterfactual explanations.
Inf. Sci., January, 2024

Using Curiosity for an Even Representation of Tasks in Continual Offline Reinforcement Learning.
Cogn. Comput., January, 2024

2023
Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation.
Inf. Fusion, November, 2023

Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence.
Inf. Fusion, November, 2023

Correction to: Feature contribution alignment with expert knowledge for artificial intelligence credit scoring.
Signal Image Video Process., June, 2023

Gender and sex bias in COVID-19 epidemiological data through the lens of causality.
Inf. Process. Manag., May, 2023

Responsible and human centric AI-based insurance advisors.
Inf. Process. Manag., May, 2023

Feature contribution alignment with expert knowledge for artificial intelligence credit scoring.
Signal Image Video Process., March, 2023

Towards a more efficient computation of individual attribute and policy contribution for post-hoc explanation of cooperative multi-agent systems using Myerson values.
Knowl. Based Syst., 2023

Credit Risk Scoring Using a Data Fusion Approach.
Proceedings of the Computational Collective Intelligence - 15th International Conference, 2023

2022
Explaining <i>Aha!</i> moments in artificial agents through IKE-XAI: Implicit Knowledge Extraction for eXplainable AI.
Neural Networks, 2022

Greybox XAI: A Neural-Symbolic learning framework to produce interpretable predictions for image classification.
Knowl. Based Syst., 2022

PLENARY: Explaining black-box models in natural language through fuzzy linguistic summaries.
Inf. Sci., 2022

EXplainable Neural-Symbolic Learning (<i>X-NeSyL</i>) methodology to fuse deep learning representations with expert knowledge graphs: The MonuMAI cultural heritage use case.
Inf. Fusion, 2022

Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence.
Inf. Fusion, 2022

Exploring the Trade-off between Plausibility, Change Intensity and Adversarial Power in Counterfactual Explanations using Multi-objective Optimization.
CoRR, 2022

Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning With Shapley Values.
IEEE Comput. Intell. Mag., 2022

OG-SGG: Ontology-Guided Scene Graph Generation - A Case Study in Transfer Learning for Telepresence Robotics.
IEEE Access, 2022

Sectorial Analysis Impact on the Development of Credit Scoring Machine Learning Models.
Proceedings of the 14th International Conference on Management of Digital EcoSystems, 2022

On Young Children's Exploration, Aha! Moments and Explanations in Model Building for Self-Regulated Problem-Solving.
Proceedings of the Workshop on AI Evaluation Beyond Metrics co-located with the 31st International Joint Conference on Artificial Intelligence (IJCAI-ECAI 2022), 2022

Capabilities, Limitations and Challenges of Style Transfer with CycleGANs: A Study on Automatic Ring Design Generation.
Proceedings of the Machine Learning and Knowledge Extraction, 2022

2021
Explainability in deep reinforcement learning.
Knowl. Based Syst., 2021

Efficient State Representation Learning for Dynamic Robotic Scenarios.
CoRR, 2021

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.
CoRR, 2021

EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case.
CoRR, 2021

Physically-Consistent Generative Adversarial Networks for Coastal Flood Visualization.
CoRR, 2021

Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey.
CoRR, 2021

Explaining Credit Risk Scoring through Feature Contribution Alignment with Expert Risk Analysts.
CoRR, 2021

2020
Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges.
Inf. Fusion, 2020

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI.
Inf. Fusion, 2020

Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities.
Frontiers Big Data, 2020

Physics-informed GANs for Coastal Flood Visualization.
CoRR, 2020

Should artificial agents ask for help in human-robot collaborative problem-solving?
CoRR, 2020

DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics.
CoRR, 2020

Egoshots, an ego-vision life-logging dataset and semantic fidelity metric to evaluate diversity in image captioning models.
CoRR, 2020

Accessible Cultural Heritage through Explainable Artificial Intelligence.
Proceedings of the Adjunct Publication of the 28th ACM Conference on User Modeling, 2020

2019
RDF Stores for Enhanced Living Environments: An Overview.
Proceedings of the Enhanced Living Environments, 2019

Highlighting Bias with Explainable Neural-Symbolic Visual Reasoning.
CoRR, 2019

DisCoRL: Continual Reinforcement Learning via Policy Distillation.
CoRR, 2019

Continual Learning for Robotics.
CoRR, 2019

Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer.
CoRR, 2019

Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics.
CoRR, 2019

Towards Explainable Neural-Symbolic Visual Reasoning.
Proceedings of the 2019 International Workshop on Neural-Symbolic Learning and Reasoning (NeSy 2019), 2019

Deep unsupervised state representation learning with robotic priors: a robustness analysis.
Proceedings of the International Joint Conference on Neural Networks, 2019

2018
State representation learning for control: An overview.
Neural Networks, 2018

Open-Ended Learning: A Conceptual Framework Based on Representational Redescription.
Frontiers Neurorobotics, 2018

Intelligent Drone Swarm for Search and Rescue Operations at Sea.
CoRR, 2018

Don't forget, there is more than forgetting: new metrics for Continual Learning.
CoRR, 2018

S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning.
CoRR, 2018

Datil: Learning Fuzzy Ontology Datatypes.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations, 2018

2017
Unsupervised understanding of location and illumination changes in egocentric videos.
Pervasive Mob. Comput., 2017

Unsupervised state representation learning with robotic priors: a robustness benchmark.
CoRR, 2017

Couch potato or gym addict? Semantic lifestyle profiling with wearables and knowledge graphs.
Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017

2016
Semantic and fuzzy modelling for human behaviour recognition in smart spaces: a case study on ambient assisted living.
PhD thesis, 2016

Validation Techniques for Sensor Data in Mobile Health Applications.
J. Sensors, 2016

An Ontology for Wearables Data Interoperability and Ambient Assisted Living Application Development.
Proceedings of the Recent Developments and the New Direction in Soft-Computing Foundations and Applications, 2016

A semantic security framework and context-aware role-based access control ontology for smart spaces.
Proceedings of the International Workshop on Semantic Big Data, 2016

2015
Smart Dosing: A mobile application for tracking the medication tray-filling and dispensation processes in hospital wards.
Proceedings of the Recent Advances in Ambient Assisted Living, 2015

2014
Erratum to: Exploiting smart spaces for interactive TV applications development.
J. Supercomput., 2014

Handling Real-World Context Awareness, Uncertainty and Vagueness in Real-Time Human Activity Tracking and Recognition with a Fuzzy Ontology-Based Hybrid Method.
Sensors, 2014

A fuzzy ontology for semantic modelling and recognition of human behaviour.
Knowl. Based Syst., 2014

Can IT health-care applications improve the medication tray-filling process at hospital wards? An exploratory study using eye-tracking and stress response.
Proceedings of the 16th IEEE International Conference on e-Health Networking, 2014

2013
A survey on ontologies for human behavior recognition.
ACM Comput. Surv., 2013

Understanding Movement and Interaction: An Ontology for Kinect-Based 3D Depth Sensors.
Proceedings of the Ubiquitous Computing and Ambient Intelligence. Context-Awareness and Context-Driven Interaction, 2013

An approach to improve semantics in Smart Spaces using reactive fuzzy rules.
Proceedings of the Joint IFSA World Congress and NAFIPS Annual Meeting, 2013

Rapid prototyping of semantic applications in smart spaces with a visual rule language.
Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2013

Extending Semantic Web Tools for Improving Smart Spaces Interoperability and Usability.
Proceedings of the Distributed Computing and Artificial Intelligence, 2013

2011
Programming biomedical smart space applications with <i>BioImageXD</i> and <i>PythonRules</i>.
Proceedings of the 4th International Workshop on Semantic Web Applications and Tools for the Life Sciences, 2011

A Framework for Context-Aware Applications for Smart Spaces.
Proceedings of the 11th Annual International Symposium on Applications and the Internet, 2011

A Framework for Context-Aware Applications for Smart Spaces.
Proceedings of the Smart Spaces and Next Generation Wired/Wireless Networking, 2011


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