Abstract: Graph Convolutional Networks (GCNs) have been widely studied for semi-supervised learning tasks. It is known that the graph convolution operations in most of existing GCNs are composed of ...

Abstract: We present ENCoRP, a tool for computing and visualizing the frequency-domain conductive and radiative propagation associated with an injected signal traversing a user-defined electrical ...

D-Tools has launched Interconnect Diagrams in D-Tools Cloud, a new feature that gives integrators an intelligent, visual way to design and document signal flow and wire connections with complete ...

Researchers at the VIB-UAntwerp Center for Molecular Neurology have visualized how brain network development is altered in a model of KCNQ2-related developmental and epileptic encephalopathy, a rare ...

When Nick Watkins was a child, he pasted articles about space exploration into scrapbooks and drew annotated diagrams of rockets. He knew this because, years later, he still had the scrapbooks, and ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...

In this tutorial, we implement the BioCypher AI Agent, a powerful tool designed for building, querying, and analyzing biomedical knowledge graphs using the BioCypher framework. By combining the ...

Imagine standing atop a mountain, gazing at the vast landscape below, trying to make sense of the world around you. For centuries, explorers relied on such vantage points to map their surroundings.

A one-slide representation is the best way to win over employees and investors. by João Cotter Salvado and Freek Vermeulen On December 1, 2014, Cypress Semiconductor announced that it was acquiring ...