• What kind of content are you prone to tweet?: multi-topic preference model for tweeters

  Recalde, Lorena; Baeza Yates, Ricardo (Springer, 2020)

  According to tastes, a person could show preference for a given category of content to a greater or lesser extent. However, quantifying people’s amount of interest in a certain topic is a challenging task, especially ...
• NEVAE: a deep generative model for molecular graphs

  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 ...
• Vision affects how fast we hear sounds move

  López-Moliner, Joan; Soto Faraco, Salvador (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 ...
• Can the occipital alpha-phase speed up visual detection through a real-time EEG-based brain-computer interface (BCI)?

  Vigué Guix, Irene; Morís Fernández, Luis, 1982-; Torralba Cuello, Mireia; Ruzzoli, Manuela; Soto Faraco, Salvador (Wiley, 2020)

  Electrical brain oscillations reflect fluctuations in neural excitability. Fluctuations in the alpha band (α, 8–12 Hz) in the occipito‐parietal cortex are thought to regulate sensory responses, leading to cyclic variations ...
• In nobody's name: a checks and balances approach to international judicial independence

  Torres Pérez, Aida (Nomos, 2020)

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