Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around ...

Have you ever examined timber floorboards and pondered why they look the way they do? Perhaps you admired the super-fine ...

The agentic AI solution, known internally as Weave, launched alongside a model benchmarking tool called LLM-IQ. It was built from the ground up using data sourced from carriers and operators to create ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph ...

A new framework to track the structure of temporal networks with a signal processing approach is introduced. The method is based on the duality between static networks and signals, obtained using a ...

Graph neural network (GNN) models are increasingly being used for the classification of electroencephalography (EEG) data. However, GNN-based diagnosis of neurological disorders, such as Alzheimer’s ...

DCGCN decomposes the 3D point cloud data of a molecule into three components: atomic sequence, atomic connectivity, and a distance map. From its connectivity and distance information, DCGCN captures ...

Security graphs are becoming indispensable for understanding system access and network activity and empowering security teams to anticipate, detect and contain breaches.

Population structure limits the use of genomic data for predicting phenotypes and managing genetic resources in forest trees ...