SOCO - Soft Computing: Enviaments recents

Ara es mostren els items 1-12 de 258

    • A deep learning-based method for uncovering GPCR ligand-induced conformational states using interpretability techniques 

      Gutiérrez Mondragón, Mario Alberto; König, Caroline; Vellido Alcacena, Alfredo (Springer, 2022)
      Text en actes de congrés
      Accés obert
      There is increasing interest in the development of tools for investigating the protein ligand space. Understanding the underlying mechanisms of G protein-coupled receptors (GPCR) in the ligand-binding process is of particular ...

    • The importance of interpretability and visualization in ML for medical applications 

      Vellido Alcacena, Alfredo (2021)
      Comunicació de congrés
      Accés obert
      Many areas of science have made a sharp transition towards data-dependent methods, enabled by simultaneous advances in data acquisition and the development of networked system technologies. This is particularly clear in ...

    • Informàtica bàsica II, ETSEIB. Memòria del curs 1994-1995 

      Vila Marta, Sebastià; Pla García, Núria; Soto Riera, Antoni; Pérez Vidal, Lluís; Roura Ferret, Salvador; Franquesa Niubó, Marta; Cotrina Navau, Josep; Alquézar Mancho, René; Martínez Parra, Conrado (1995-02-06)
      Report de recerca
      Accés obert
      Memòria de l'assignatura d'Infomàtica bàsica II del curs 94-95.

    • LONG-REMI: An AI-based technological application to promote healthy mental longevity grounded in reminiscence therapy 

      Nebot Castells, M. Àngela; Domenech Pou, Sara; Albino-Pires, Natália; Múgica Álvarez, Francisco; Benali, Anass; Porta, Xènia; Nebot Mugica, Oriol; Santos, Pedro M. (2022-05-15)
      Article
      Accés obert
      Reminiscence therapy (RT) consists of thinking about one’s own experiences through the presentation of memory-facilitating stimuli, and it has as its fundamental axis the activation of emotions. An innovative way of offering ...

    • The coming of age of interpretable and explainable machine learning models 

      Lisboa, Paulo; Saralajew, Sascha; Vellido Alcacena, Alfredo; Villmann, Thomas (I6doc.com, 2021)
      Text en actes de congrés
      Accés obert
      Machine learning-based systems are now part of a wide array of real-world applications seamlessly embedded in the social realm. In the wake of this realisation, strict legal regulations for these systems are currently being ...

    • Tracking a well diversified portfolio with maximum entropy in the mean 

      Arratia Quesada, Argimiro Alejandro; Gzyl, Henryk; Mayoral Blaya, Silvia (Multidisciplinary Digital Publishing Institute (MDPI), 2022-02)
      Article
      Accés obert
      In this work we address the following problem: Having chosen a well diversified portfolio, we show how to improve on its return, maintaining the diversification. In order to achieve this boost on return we construct a ...

    • Misreported longitudinal data in epidemiology: review of mixture-based advances and current challenges 

      Moriña, David; Fernandez Fontelo, Amanda; Cabaña Nigro, Ana Alejandra; Arratia Quesada, Argimiro Alejandro; Puig Casado, Pere (2021-12)
      Article
      Accés obert
      The problem of dealing with misreported data is very common in a wide range of contexts and for different reasons. This has been and still is an important issue for data analysts and statisticians as not accounting for it ...

    • Forest fire forecasting using fuzzy logic models 

      Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (2021-07-29)
      Article
      Accés obert
      In this study, we explored hybrid fuzzy logic modelling techniques to predict the burned area of forest fires. Fast detection is crucial for successful firefighting, and a model with an accurate prediction ability is ...

    • Off-the-grid: Fast and effective hyperparameter search for kernel clustering 

      Ordozgoiti Rubio, Bruno; Belanche Muñoz, Luis Antonio (Springer, 2020)
      Text en actes de congrés
      Accés obert
      Kernel functions are a powerful tool to enhance the k-means clustering algorithm via the kernel trick. It is known that the parameters of the chosen kernel function can have a dramatic impact on the result. In supervised ...

    • Predicciones financieras basadas en análisis de sentimiento de textos y minería de opiniones 

      Arratia Quesada, Argimiro Alejandro (FUNCAS, 2021-04-01)
      Capítol de llibre
      Accés restringit per política de l'editorial
      En este capítulo se describe la mecánica básica para construir un modelo de predicción que utiliza indicadores de sentimiento derivados de datos textuales. Enfocamos nuestro objetivo de predicciones en series de ...

    • Cumulated burden of Covid-19 in Spain from a Bayesian perspective 

      Moriña, David; Fernandez Fontelo, Amanda; Cabaña Nigro, Ana Alejandra; Arratia Quesada, Argimiro Alejandro; Ávalos Villaseñor, Gustavo Eduardo; Puig, Pedro (2021-12)
      Article
      Accés obert
      Background The main goal of this work is to estimate the actual number of cases of Covid-19 in Spain in the period 01-31-2020/06-01-2020 by Autonomous Communities. Based on these estimates, this work allows us to accurately ...

    • kernInt: A kernel framework for integrating supervised and unsupervised analyses in spatio-temporal metagenomic datasets 

      Ramon Gurrea, Elies; Belanche Muñoz, Luis Antonio; Molist Gasa, Francesc; Quintanilla Aguado, Raquel; Pérez Enciso, Miguel; Ramayo Caldas, Yuliaxis (2021-01-28)
      Article
      Accés obert
      The advent of next-generation sequencing technologies allowed relative quantification of microbiome communities and their spatial and temporal variation. In recent years, supervised learning (i.e., prediction of a phenotype ...