The last ten years of attention research have witnessed a revolution, replacing a theoretical
dichotomy (top-down vs. bottom-up control) with a trichotomy (biased by current goals …

Recently it was argued that in addition to top-down and bottom-up processes, lingering
biases of selection history play a major role in visual selection (Awh, Belopolsky & …

We introduce the GANsformer, a novel and efficient type of transformer, and explore it for the
task of visual generative modeling. The network employs a bipartite structure that enables …

Deep learning models are vulnerable to adversarial examples. As a more threatening type
for practical deep learning systems, physical adversarial examples have received extensive …

Understanding and predicting the human visual attention mechanism is an active area of
research in the fields of neuroscience and computer vision. In this paper, we propose …

There is growing consensus that reward plays an important role in the control of attention.
Until recently, reward was thought to influence attention indirectly by modulating task …

Data stream mining is an active research area that has recently emerged to discover
knowledge from large amounts of continuously generated data. In this context, several data …

The brain is limited in its capacity to process all sensory stimuli present in the physical world
at any point in time and relies instead on the cognitive process of attention to focus neural …

The present paper argues for the notion that when attention is spread across the visual field
in the first sweep of information through the brain visual selection is completely stimulus …

The problem of consciousness continues to be a subject of great debate in cognitive
science. Synthesizing decades of research, The Conscious Brain advances a new theory of …