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Gonzalo Nápoles

Biographic Data

ID8970864
NAMEGonzalo Nápoles
GIVEN NAMESGonzalo
FAMILY NAMENápoles
SIGNATURENÁPOLES G
AFFILIATIONSTilburg University
ORCID0000-0003-1936-3701
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS0
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2025
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Modeling depression trends through continuous cognitive mapping

    Open Access•Konstantina Lampropoulou, Gonzalo Nápoles et al.•ARTICLE•SSM - Mental Health•2026

    Modeling the global burden of depression presents significant challenges due to the chronic, dynamic, and heterogeneous nature of the disease. While Fuzzy Cognitive Maps (FCMs) provide an interpretable framework for modeling relational dynamics, conventional formulations often suffer from numerical saturation and a limited ability to capture structurally diverse solution spaces. In this paper, we propose a Continuous Fuzzy Cognitive Map (cFCM) fr…

  • Mitigating implicit and explicit bias in structured data without sacrificing accuracy in pattern classification

    Open Access•Fabian Hoitsma, Gonzalo Nápoles et al.•ARTICLE•AI & Society•2025

    Using biased data to train Artificial Intelligence (AI) algorithms will lead to biased decisions, discriminating against certain groups or individuals. Bias can be explicit (one or several protected features directly influence the decisions) or implicit (one or several protected features indirectly influence the decisions). Unsurprisingly, biased patterns are difficult to detect and mitigate. This paper investigates the extent to which explicit a…

No prominent works on this page.

  • Mitigating implicit and explicit bias in structured data without sacrificing accuracy in pattern classification

    Open Access•Fabian Hoitsma, Gonzalo Nápoles et al.•ARTICLE•AI & Society•2025

    Using biased data to train Artificial Intelligence (AI) algorithms will lead to biased decisions, discriminating against certain groups or individuals. Bias can be explicit (one or several protected features directly influence the decisions) or implicit (one or several protected features indirectly influence the decisions). Unsurprisingly, biased patterns are difficult to detect and mitigate. This paper investigates the extent to which explicit a…

  • Modeling depression trends through continuous cognitive mapping

    Open Access•Konstantina Lampropoulou, Gonzalo Nápoles et al.•ARTICLE•SSM - Mental Health•2026

    Modeling the global burden of depression presents significant challenges due to the chronic, dynamic, and heterogeneous nature of the disease. While Fuzzy Cognitive Maps (FCMs) provide an interpretable framework for modeling relational dynamics, conventional formulations often suffer from numerical saturation and a limited ability to capture structurally diverse solution spaces. In this paper, we propose a Continuous Fuzzy Cognitive Map (cFCM) fr…

Artificial Intelligence (1 work) · Categorization (1 work) · Centrality (1 work) · Cluster analysis (1 work) · Cognition (1 work) · Cognitive map (1 work) · Cognitive psychology (1 work) · Cognitive Science and Mapping (1 work) · Computer Science (1 work) · Data mining (1 work)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae