A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account ...

As you explore how to create new opportunities with AI, it’s crucial to first take a close look at your data architecture.

Artificial intelligence has taken the world by storm. In biology, AI tools called deep neural networks (DNNs) have proven invaluable for predicting the results of genomic experiments. Their usefulness ...

It’s more than just code. Scientists have found a way to "dial" the hidden personalities of AI, from conspiracy theorists to ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Abstract: Geometric Deep Learning is a modern approach to deep learning that focuses on the assessment of the structure and inherent symmetry of the data. How to best represent Electrocardiogram (ECG) ...

Abstract: Graph embeddings map graph-structured data into vector spaces for machine learning tasks. In Graph Neural Networks (GNNs), these embeddings are computed through message passing and support ...

The University of Pennsylvania has confirmed that a hacker breached numerous internal systems related to the university's development and alumni activities and stole data in a cyberattack. In a new ...

Alzheimer's Disease (AD), a leading neurodegenerative disorder, presents significant global health challenges. Advances in graph neural networks (GNNs) offer promising tools for analyzing multimodal ...

Power availability and infrastructure delivery timelines are making it extremely difficult for data center inventory to keep up with demand. The data center market in North America continues to grow ...

Finnegan’s Lynn Parker Dupree and Baker McKenzie’s Lothar Determann discuss a wave of new state laws regarding brainwaves tracked by wearable devices, or data derived from the activity of a person’s ...