CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Deliverables
This deliverable concerns a status report on the technical achievements of TRUST in the first nine months of the projects A brief description of the development of each task will be provided including documentation of procedures screenshots preliminary results and identified risks
Data management plan V2 (opens in new window)Final validation of the learned explainable AI models (online retail) (opens in new window)
In this deliverable, a final validation of the proposed approach will be provided. The results and final conclusions of the online retail use case will be described together with lessons learned and recommendations for future developments.
Final validation of the learned explainable AI models for the energy use case (opens in new window)In this deliverable, a final validation of the proposed approach will be provided. The results and final conclusions of the energy use case will be described together with lessons learned and recommendations for future developments.
Saliency measures for identifying causally variables of explanations (opens in new window)This report will present the saliency measures and code for identifying causally relevant variables of humanlike explanations The relevant variables are those to be considered during the discovery and communication of causal explanations These variables will be formalised and measurable in terms of their specificity insensitivity proximity and other characteristics known to be preferred by humans
User studies on the realization of explanations (opens in new window)The deliverable reports the result of the qualitative studies on the best way to present explanation content produced in WP3 and provides recommendations for Task 22
Communication & Dissemination report (opens in new window)This deliverable will present a final status on the achievement of the project objectives in terms of communication and dissemination. The report will refer to the KPIs proposed on Deliverable D8.1.
Evaluation by human observers of different explainability formats (opens in new window)This deliverable reports the results of the evaluation of explainability performed in Task2.3.
Final validation of the learned explainable AI models (healthcare) (opens in new window)In this deliverable, a final validation of the proposed approach will be provided. The results and final conclusions of the healthcare use case will be described together with lessons learned and recommendations for future developments.
Data management plan V3 (opens in new window)Dialog WP4-WP3 (opens in new window)
In this deliverable, the results of the interaction between WP4 and WP3 will be presented. The final outcome is the generation of explainable expressions by iterated dialog with the user in the proposed toy problems.
Exploitation Plan (opens in new window)This report described the future exploration of the framework, detailed in Task 8.3.Partners will consolidate all relevant findings, identify risks and evaluate the potential applicability of TRUST components in different sectors, covering many aspects of AI.
Communication & Dissemination update (opens in new window)This deliverable will present an updated status of the CDP, reporting the achievements obtained for each KPI and possible necessary changes to the plan.
Framework requirements document (opens in new window)This deliverable will describe the functional and nonfunctional requirements of the framework as well as the interactions and dependencies between the building blocks The use case needs will also be detailed and reported in this document ensuring that the framework is adequate to different problems and sectors
Communication & Dissemination plan (opens in new window)This report will present the Communication Dissemination Plan of TRUST where the strategy to raise public awareness about the project outcomes will be detailed and scheduled In addition to academic publications and conferences the plan includes events promotion participation in working groups and online forums and educational content creation such as courseware and webinars The plan will include KPIs and their target values as well as the Partner responsible for each communicationdissemination method
Evaluation with healthcare experts of learned models (opens in new window)This deliverable concerns a formal validation of the AI models developed for the first simplified version of the healthcare problem These models will be designed by NWOI and validated by medical experts from LUMC The report will present the first insights on the models results and suggestions for modifications
Initial validation of the explainable AI models from business experts (opens in new window)This deliverable concerns a formal validation of the AI models developed for the first simplified version of the online retail problem These models will be designed by LTP and validated by practitioners from Sonae INESC will coordinate the development and validation process
Data management plan (opens in new window)This deliverable presents the Data Management Plan of TRUSTAI detailing the types of data generatedcollected how it will be exploited protected and the standards to be considered
Framework validation (opens in new window)This deliverable consolidates the final conclusions from the use cases and describes the primary outcomes of TRUST framework. Recommendations for future extensions will also be included.
Initial validation of the explainable AI models from energy experts (opens in new window)This deliverable concerns a formal validation of the AI models developed for the first simplified version of the energy problem These models will be designed by POLIS21 and validated by practitioners from the industry
This deliverable concerns the automated image analysis learning techniques integrated with TRUST blocks.
Project website (opens in new window)This deliverable will present the specification, organization and features of TRUST-AI website. The DNS, URL to access and screenshots on each page will also be presented.
Publications
Author(s):
M. Virgolin and P.A.N. Bosman
Published in:
GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022, Page(s) 2289–2297
Publisher:
ACM
DOI:
10.1145/3520304.3534036
Author(s):
Miguel Lunet, Daniela Fernandes, Fábio Neves-Moreira, Pedro Amorim
Published in:
GECCO '25: Genetic and Evolutionary Computation Conference, 2025
Publisher:
Digital Library
Author(s):
Videau, Mathurin; Ferreira Leite, Alessandro; Teytaud, Olivier; Schoenauer, Marc
Published in:
EUROGP - 25th European Conference on Genetic Programming, part of EvoStar 2022, Issue 25, 2022, Page(s) pp.278-293, ISBN 978-3-031-02055-1
Publisher:
Springer Verlag
DOI:
10.1007/978-3-031-02056-8_18
Author(s):
Eduard Barbu, Marharytha Domnich, Raul Vicente, Nikos Sakkas, André Morim
Published in:
The 2nd World Conference on eXplainable Artificial Intelligence (xAI 2024), July 17-19, 2024 - Valletta, Malta, 2024
Publisher:
Springer
DOI:
10.48550/arxiv.2405.11958
Author(s):
Sijben, Evi; Alderliesten, Tanja; Bosman, Peter
Published in:
GECCO '22: Genetic and Evolutionary Computation Conference, 2022, ISBN 978-1-4503-9237-2
Publisher:
Association for Computing Machinery, New York, NY, United States
DOI:
10.48550/arxiv.2203.13347
Author(s):
Alessandro Leite and Marc Schoenauer
Published in:
26th EuroGP - Part of EvoStar 2023, Issue 26, 2023, Page(s) 198–212, ISBN 978-3-031-29572-0
Publisher:
Springer Verlag LNCS-13986
DOI:
10.1007/978-3-031-29573-7_13
Author(s):
Poinsot, Audrey; Leite, Alessandro
Published in:
Workshop on the pitfalls of limited data and computation for Trustworthy ML, ICLR 2023, 2023
Publisher:
OpenReview
DOI:
10.48550/arxiv.2304.01237
Author(s):
Oriol Corcoll and Raul Vicente
Published in:
Issue 26403498, 2022, ISSN 2640-3498
Publisher:
Proceedings of Machine Learning Research
Author(s):
Evi Sijben, Jeroen Jansen, Peter Bosman, Tanja Alderliesten
Published in:
Proceedings of the Genetic and Evolutionary Computation Conference, 2024, Page(s) 1354-1362
Publisher:
ACM
DOI:
10.1145/3638529.3654145
Author(s):
Labash, Aqeel; Fletzer, Florian; Majoral, Daniel; Vicente, Raul
Published in:
ICML'23: Proceedings of the 40th International Conference on Machine Learning, Issue 18, 2023
Publisher:
JMLR.org
DOI:
10.48550/arxiv.2307.12143
Author(s):
Dmytro Shvetsov, Joonas Ariva, Marharyta Domnich, Raul Vicente, Dmytro Fishman
Published in:
The 2nd World Conference on eXplainable Artificial Intelligence (xAI 2024), July 17-19, 2024 - Valletta, Malta, 2024
Publisher:
Springer
DOI:
10.48550/arxiv.2404.12832
Author(s):
Fábio Neves-Moreira, Daniela Fernandes, Miguel Lunet, Pedro Amorim
Published in:
IJCAI 2024 - International Joint Conference on Artificial Intelligence, Jeju, South Korea, 2024
Publisher:
IJCAI
Author(s):
E.M.C. Sijben, J.C. Jansen, P.A.N. Bosman (Peter), and T. Alderliesten
Published in:
Proceedings Volume 12929, Medical Imaging 2024: Image Perception, Observer Performance, and Technology Assessment, 2024, Page(s) 1292916
Publisher:
SPIE
DOI:
10.1117/12.3006413
Author(s):
Marharyta Domnich, Raul Vicente
Published in:
The 2nd World Conference on eXplainable Artificial Intelligence (xAI 2024), July 17-19, 2024 - Valletta, Malta, 2024
Publisher:
Springer
DOI:
10.48550/arxiv.2404.12810
Author(s):
N. Sakkas, M. Papadopoulou, D. Sakkas
Published in:
WDBE 2021, 2021
Publisher:
World of Digital Built Environment WDBE 2021
Author(s):
Dazhuang Liu, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman
Published in:
GECCO '22: Genetic and Evolutionary Computation Conference, 2022
Publisher:
Association for Computing Machinery, New York, NY, United States
DOI:
10.1145/3512290.3528787
Author(s):
Mariana Casalta, Flávia Barbosa, Luciana Yamada, Lígia B. Ramos
Published in:
Utilities Policy, Issue 91, 2024, Page(s) 101822, ISSN 0957-1787
Publisher:
Pergamon Press Ltd.
DOI:
10.1016/j.jup.2024.101822
Author(s):
Aru, Jaan; Labash, Aqeel; Corcoll, Oriol; Vicente, Raul
Published in:
Artificial Ingtelligence Review, Issue 3, 2023, ISSN 0269-2821
Publisher:
Kluwer Academic Publishers
DOI:
10.1007/s10462-023-10401-x
Author(s):
Fábio Neves-Moreira, Pedro Amorim
Published in:
International Journal of Production Economics, 2024, ISSN 0925-5273
Publisher:
Elsevier BV
DOI:
10.1016/j.ijpe.2023.109074
Author(s):
Cristiane Ferreira, Gonçalo Figueira, Pedro Amorim, Alexandre Pigatti
Published in:
Computers & Operations Research, 2023, ISSN 0305-0548
Publisher:
Pergamon Press Ltd.
DOI:
10.1016/j.cor.2023.106364
Author(s):
Sakkas, N., Yfanti, S
Published in:
Academia Letters, 2021, ISSN 2771-9359
Publisher:
Academia.edu
DOI:
10.20935/al3629
Author(s):
Marharyta Domnich, Julius Välja, Rasmus Moorits Veski, Giacomo Magnifico, Kadi Tulver, Eduard Barbu, Raul Vicente
Published in:
Proceedings of the AAAI Conference on Artificial Intelligence, Issue 39, 2025, Page(s) 16308-16316, ISSN 2374-3468
Publisher:
Association for the Advancement of Artificial Intelligence (AAAI)
DOI:
10.1609/aaai.v39i15.33791
Author(s):
Alessandro Leite, Marc Schoenauer
Published in:
Genetic Programming and Evolvable Machines, Issue 26, 2025, ISSN 1389-2576
Publisher:
Kluwer Academic Publishers
DOI:
10.1007/s10710-024-09506-1
Author(s):
Nikos Sakkas, Sofia Yfanti,Pooja Shah, Nikitas Sakkas, Christina Chaniotakis, Costas Daskalakis, Eduard Barbu and Marharyta Domnich
Published in:
Energies, 2023, ISSN 1996-1073
Publisher:
Multidisciplinary Digital Publishing Institute (MDPI)
DOI:
10.3390/en16207210
Author(s):
Stelzer, Florian; Röhm, André; Vicente, Raul; Fischer, Ingo; Yanchuk, Serhiy
Published in:
Nature Communications, Issue 20411723, 2021, ISSN 2041-1723
Publisher:
Nature Publishing Group
DOI:
10.48550/arxiv.2011.10115
Author(s):
Sofia Yfanti, Nikos Sakkas
Published in:
Applied System Innovation, 2024, ISSN 2571-5577
Publisher:
MDPI
DOI:
10.3390/asi7020032
Author(s):
Yannik Zeiträg, José Rui Figueira, Gonçalo Figueira
Published in:
International Journal of Production Research, 2024, ISSN 0925-5273
Publisher:
Elsevier BV
DOI:
10.1080/00207543.2023.2301044
Author(s):
Nikos Sakkas, Christina Chaniotaki and Nikitas Sakkas
Published in:
IOP Conference Series: Earth and Environmental Science, 2023, ISSN 1757-899X
Publisher:
IOP Science
DOI:
10.1088/1755-1315/1122/1/012066
Author(s):
Özden Gür Ali, Pedro Amorim
Published in:
International Journal of Forecasting, 2024, Page(s) 706-720, ISSN 0169-2070
Publisher:
Elsevier BV
DOI:
10.1016/j.ijforecast.2023.04.008
Author(s):
Anti Ingel, Abdullah Makkeh, Oriol Corcoll and Raul Vicente
Published in:
Entropy, Issue 10994300, 2022, ISSN 1099-4300
Publisher:
Multidisciplinary Digital Publishing Institute (MDPI)
DOI:
10.3390/e24030401
Author(s):
Nikos Sakkas; Sofia Yfanti; Costas Daskalakis; Eduard Barbu; Marharyta Domnich
Published in:
Energies, Issue 1, 2021, ISSN 1996-1073
Publisher:
Multidisciplinary Digital Publishing Institute (MDPI)
DOI:
10.3390/en14206568
Author(s):
Tambet Matiisen; Aqeel Labash; Daniel Majoral; Jaan Aru; Raul Vicente
Published in:
Stats, Vol 6, Iss 1, Pp 50-66 (2022), Issue 5, 2022, ISSN 2571-905X
Publisher:
MDPI
DOI:
10.3390/stats6010004
Author(s):
Sakkas, N., Athanasiou, N.
Published in:
Academia Letters, Issue 27719359, 2021, ISSN 2771-9359
Publisher:
Academia.edu
DOI:
10.20935/al3451
Author(s):
Catarina Furtado Martins da Rocha Leite
Published in:
2022
Publisher:
University of Porto
Author(s):
Álvaro Manuel Festas Pereira da Silva
Published in:
2021
Publisher:
University of Porto
Author(s):
Luís Pedro Viana Ramos
Published in:
2022
Publisher:
University of Porto
Author(s):
João Rafael Gomes Varela
Published in:
2022
Publisher:
University of Porto
Author(s):
Johannes Koch, Tanja Alderliesten, Peter A. N. Bosman
Published in:
Lecture Notes in Computer Science, Parallel Problem Solving from Nature – PPSN XVIII, 2024, Page(s) 238-255
Publisher:
Springer Nature Switzerland
DOI:
10.1007/978-3-031-70055-2_15
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