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 ...

Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...

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) ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...

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 ...

BELLEVUE, Wash.--(BUSINESS WIRE)--Smartsheet, the Intelligent Work Management platform that unites people, data and AI, today announced the next major evolution of its platform, unveiling a powerful ...

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 ...

Info-Tech Research Group has released a new resource to help organizations tackle the growing challenges of data discovery and classification. The blueprint, titled Discover and Classify Your Data, ...