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Articles (Departament de Tecnologies de la Informació i les Comunicacions)

Articles (Departament de Tecnologies de la Informació i les Comunicacions)

 

Articles de recerca, en accés obert, del Departament de Tecnologies de la Informació i de les Comunicacions de la UPF.

Recent Submissions

  • Byers Heinlein, Krista; Ka-Ying Tsui, Rachel; Van Renswoude, Daan; Black, Alexis K; Barr, Rachel; Brown, Anna; Colomer, Marc; Durrant, Samantha; Gampe, Anja; Gonzalez Gomez, Nayeli; Hay, Jessica F; Hernik, Mikolaj; Jartó, Marianna; Melinda Kovács, Ágnes; Laoun Rubenstein, Alexandra; Lew Williams, Casey; Liszkowski, Ulf; Liu, Liquan; Noble, Claire; Potter, Christine E; Rocha Hidalgo, Joscelin; Sebastián Gallés, Núria; Soderstrom, Melanie; Visser, Ingmar; Waddell, Connor; Wermelinger, Stephanie; Singh, Leher (Wiley, 2020)
    Determining the meanings of words requires language learners to attend to what other people say. However, it behooves a young language learner to simultaneously encode relevant non-verbal cues, for example, by following ...
  • Mosayebi, Reza; Mojahedian, Mohammad Mahdi; Lozano Solsona, Angel (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Drawing on the notion of parallel interference cancellation, this paper formulates a one-shot linear receiver for the uplink of centralized, possibly cloud-based, radio access networks (C-RANs) operating in a cell-free ...
  • Nikbakht, Rasoul; Jonsson, Anders, 1973-; Lozano Solsona, Angel (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    This letter applies a feedforward neural network trained in an unsupervised fashion to the problem of optimizing the transmit powers in cellular wireless systems. Both uplink and downlink are considered, with either ...
  • Nikbakht, Rasoul; Jonsson, Anders, 1973-; Lozano Solsona, Angel (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    This letter applies a feedforward neural network trained in an unsupervised fashion to the problem of optimizing the transmit powers in centralized radio access networks operating on a cell-free basis. Both uplink and ...
  • Nikbakht, Rasoul; Jonsson, Anders, 1973-; Lozano Solsona, Angel (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    This letter proposes the unsupervised training of a feedforward neural network to solve parametric optimization problems involving large numbers of parameters. Such unsupervised training, which consists in repeatedly ...
  • Cruzat, Josephine; Torralba, Mireia; Ruzzoli, Manuela; Fernández, Alba; Deco, Gustavo; Soto-Faraco, Salvador, 1970- (Elsevier, 2021)
    Several studies have shown that attention and perception can depend upon the phase of ongoing neural oscillations at stimulus onset. Here, we extend this idea to the memory domain. We tested the hypothesis that ongoing ...
  • Piccinini, Juan; Perez Ipiña, Ignacio; Laufs, Helmut; Kringelbach, Morten L.; Deco, Gustavo; Sanz Perl, Yonatan; Tagliazucchi, Enzo (American Institute of Physics (AIP), 2021)
    An outstanding open problem in neuroscience is to understand how neural systems are capable of producing and sustaining complex spatiotemporal dynamics. Computational models that combine local dynamics with in vivo ...
  • Andrzejak, Ralph Gregor (American Institute of Physics (AIP), 2021)
    Complex-valued quadratic maps either converge to fixed points, enter into periodic cycles, show aperiodic behavior, or diverge to infinity. Which of these scenarios takes place depends on the map’s complex-valued parameter ...
  • Van Schependom, Jeroen; Vidaurre, Diego; Costers, Lars; Sjøgård, Martin; Sima, Diana M.; Smeets, Dirk; D'hooghe, Marie Beatrice; D'haeseleer, Miguel; Deco, Gustavo; Wens, Vincent; De Tiège, Xavier; Goldman, Serge; Woolrich, Mark W.; Nagels, Guy (Elsevier, 2021)
    In multiple sclerosis, the interplay of neurodegeneration, demyelination and inflammation leads to changes in neurophysiological functioning. This study aims to characterize the relation between reduced brain volumes and ...
  • Zinemanas, Pablo; Rocamora, Martín; Miron, Marius; Font Corbera, Frederic; Serra, Xavier (MDPI, 2021)
    Deep learning models have improved cutting-edge technologies in many research areas, but their black-box structure makes it difficult to understand their inner workings and the rationale behind their predictions. This may ...
  • Jancke, Dirk; Herlitze, Stefan; Kringelbach, Morten L.; Deco, Gustavo (Wiley, 2021)
    What is the effect of activating a single modulatory neuronal receptor type on entire brain network dynamics? Can such effect be isolated at all? These are important questions because characterizing elementary neuronal ...
  • Javaid, Misbah; Estivill Castro, Vladimir (MDPI, 2021)
    Typically, humans interact with a humanoid robot with apprehension. This lack of trust can seriously affect the effectiveness of a team of robots and humans. We can create effective interactions that generate trust by ...
  • Ferraro, Andrés; Favory, Xavier; Drossos, Konstantinos; Kim, Yuntae; Bogdanov, Dmitry (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Modeling various aspects that make a music piece unique is a challenging task, requiring the combination of multiple sources of information. Deep learning is commonly used to obtain representations using various sources ...
  • Dovelos, Konstantinos; Matthaiou, Michail; Ngo, Hien Quoc; Bellalta, Boris (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Terahertz (THz) communication is widely considered as a key enabler for future 6G wireless systems. However, THz links are subject to high propagation losses and inter-symbol interference due to the frequency selectivity ...
  • Coderch-Navarro, Sergi; Berjano, Enrique J.; Camara, Oscar; González-Suárez, Ana (Taylor & Francis, 2021)
    Purpose: While the standard setting during radiofrequency catheter ablation (RFCA) consists of applying low power for long times, a new setting based on high power and short duration (HPSD) has recently been suggested as ...
  • Hodzic, Amir; Bernardino Perez, Gabriel; Legallois, Damien; Gendron, Patrick; Langet, Hélène; Craene, Mathieu de; González Ballester, Miguel Ángel, 1973-; Milliez, Paul; Normand, Hervé; Bijnens, Bart; Saloux, Eric; Tournoux, Francois (MDPI, 2021)
    Few data exist concerning the right ventricular (RV) physiological adaptation in American-style football (ASF) athletes. We aimed to analyze the RV global and regional responses among ASF-trained athletes. Fifty-nine (20 ...
  • Beardsley, Marc; Albó, Laia; Aragón, Pablo; Hernández Leo, Davinia (Wiley, 2021)
    To identify factors that can contribute toward supporting educator adoption of digital technologies beyond the emergency remote teaching response to COVID‐19, we investigated how teachers’ motivation and abilities related ...
  • Furelos Blanco, Daniel; Law, Mark; Jonsson, Anders, 1973-; Broda, Krysia; Russo, Alessandra (AI Access Foundation, 2021)
    In this paper we present ISA, an approach for learning and exploiting subgoals in episodic reinforcement learning (RL) tasks. ISA interleaves reinforcement learning with the induction of a subgoal automaton, an automaton ...
  • Samanta, Bidisha; De, Abir; Jana, Gourhari; Gómez, Vicenç; Chattaraj, Pratim Kumar; Ganguly, Niloy; Gomez-Rodriguez, Manuel (Journal of Machine Learning Research, 2020)
    Deep generative models have been praised for their ability to learn smooth latent representations of images, text, and audio, which can then be used to generate new, plausible data. Motivated by these success stories, there ...
  • López-Moliner, Joan; Soto-Faraco, Salvador, 1970- (Association for Research in Vision and Ophthalmology (ARVO), 2007)
    There is a growing body of knowledge about the behavioral and neural correlates of cross-modal interactions in the perception of motion direction, as well as about the computations that underlie unimodal visual speed ...

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