Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling ...

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

The artificial intelligence community has long struggled with a fundamental challenge of making AI systems transparent and ...

In GIGNet, multi-level graph neural networks (GNNs) are utilized to extract internal graph-based features from signal samples and correlation information between different signals treated as nodes in ...

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 ...

Graph neural networks (GNN) have shown outstanding applications in fields where data is essentially represented as graphs (e.g., chemistry, biology, and recommendation systems). In this vein, ...