Abstract: Graph Neural Networks (GNNs) have emerged as a promising tool to handle data exhibiting an irregular structure. However, most GNN architectures perform well on homophilic datasets, where the ...

Author Shawn Peters blends clarity and rigor to make data structures and algorithms accessible to all learners. COLORADO, CO, UNITED STATES, January 2, 2026 /EINPresswire.com/ — Vibrant Publishers ...

Abstract: Graph neural networks (GNNs), as a cutting-edge technology in deep learning, perform particularly well in various tasks that process graph structure data. However, their foundation on ...

Icinga Web Module for Performance Data Graphs. This module enables graphs on the Host and Service Detail View for the respective performance data. The data is fetched by a "backend module", at least ...

This tool has been developed using both LM Studio and Ollama as LLM providers. The idea behind using a local LLM, like Google's Gemma-3 1B, is data privacy and low cost. In addition, with a good LLM a ...

Composite structures can be consolidated in-situ without the need for an oven or autoclave. The idea behind the technology is to eliminate the need to build such structures on Earth and then transport ...