This study uses a Bayesian framework to characterize latent brain state dynamics associated with memory encoding and performance in children, as measured with functional magnetic resonance imaging.

The peer-reviewed presentation merges computational metaphysics, algorithmic theology, and conscious hip-hop in a ...

Three new neural network-based tools enable fast, accurate alignment and annotation of images even in very wiggly subjects.

A new ‘pop-up’ device developed by Professor John Rogers lets scientists map and manipulate activity in human neural ...

Abstract: One of the fundamental scientific problems in neuroscience is to have a good understanding of how cognition and behavior emerge from brain function. Since the neuroscience concept of ...

An AI assistant that has gone viral recently is showcasing its potential to make the daily grind of countless tasks easier while also highlighting the security risks of handing over your digital life ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

AI has captured our collective imagination, promising to revolutionize scientific research, healthcare, education and medicine. The headlines are compelling: AI designs new drugs in months instead of ...

Graph Neural Networks (GNNs) are reshaping AI by enhancing data interpretation and improving applications. Learn how GNNs are crucial in advancing machine learning models. Graph Neural Networks (GNNs) ...

ABSTRACT: With the in-depth digital transformation of the global shipping industry, the accurate prediction of smart port operation efficiency has become a key factor in enhancing the competitiveness ...