Envíos recentes

  • Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends 

    Górriz, Juan M.; Álvarez-Illán, I.; Álvarez-Marquina, Agustín; Arco, Juan Eloy; Atzmueller, Martin; Ballarini, F.; Barakova, Emilia; Bologna, Guido; Duro, Richard J. Richard J. xxx; Santos Reyes, José (Elsevier, 2023-12)
    [Abstract]: Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear ...
  • M3DISEEN: A novel machine learning approach for predicting the 3D printability of medicines 

    Elbadawi, Moe; Muñiz, Brais; Gavins, Francesca K.H.; Ong, Jun Jie; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Álvaro (Elsevier B.V., 2020-11)
    [Abstract]: Artificial intelligence (AI) has the potential to reshape pharmaceutical formulation development through its ability to analyze and continuously monitor large datasets. Fused deposition modeling (FDM) ...
  • Equilibrium graphs 

    Cabalar, Pedro; Pérez Ramil, Carlos; Pérez, Gilberto (Springer, 2019)
    [Abstract]: In this paper we present an extension of Peirce’s existential graphs to provide a diagrammatic representation of expressions in Quantified Equilibrium Logic (QEL). Using this formalisation, logical connectives ...
  • Machine learning predicts 3D printing performance of over 900 drug delivery systems 

    Muñiz, Brais; Elbadawi, Moe; Ong, Jun Jie; Pollard, Thomas; Song, Zhe; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Álvaro (Elsevier B.V., 2021-09)
    [Abstract]: Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy ...
  • Forgetting Auxiliary Atoms in Forks 

    Aguado, Felicidad; Cabalar, Pedro; Fandiño, Jorge; Pearce, David; Pérez, Gilberto; Vidal, Concepción (Elsevier Ltd, 2019)
    [Abstract]: In this work we tackle the problem of checking strong equivalence of logic programs that may contain local auxiliary atoms, to be removed from their stable models and to be forbidden in any external context. ...

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