A child picks up a crayon and begins to sketch a scene from a story, not knowing that this simple act is strengthening the ...

The ability to predict brain activity from words before they occur can be explained by information shared between neighbouring words, without requiring next-word prediction by the brain.

We propose ESSC-RM, a plug-and-play Enhancing framework for Semantic Scene Completion with a Refinement Module, which can be seamlessly integrated into existing semantic scene completion (SSC) models.

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors provide convincing evidence that ...

Comorbidity—the co-occurrence of multiple diseases in a patient—complicates diagnosis, treatment, and prognosis. Understanding how diseases connect at a molecular level is crucial, especially in aging ...

Now that anyone can use AI to generate keywords and spin up a paid search campaign in minutes, it’s easy to assume the hard work is done. But creating structured, scalable performance still requires a ...

Deep learning methods such as multilayer perceptrons (MLPs) and convolutional neural networks (CNNs) have been applied to predict the complex traits in animal and plant breeding. However, it remains ...

The Semantic Timestamp Specification (SemTS) defines a convention for encoding a software's Semantic Version (SemVer) number into the last_modified timestamp of its release artifacts. - ...