Abstract: Urban traffic flow management faces increasing challenges due to accelerating urbanization. Traffic data collected from roadside sensors contain complex temporal and spatial dependencies ...

A software engineer and book author with many years of experience, I have dedicated my career to the art of automation. A software engineer and book author with many years of experience, I have ...

financial-dynamic-knowledge-graph/ ├── main.py # Main training script ├── report.md # Full project report (blog post format) ├── requirements.txt # Python dependencies │ ├── src/ │ ├── models/ │ │ ├── ...

Abstract: Graph Neural Networks (GNNs) have found widespread application in malware detection tasks in recent years, aiming to uncover the malicious nature of target processes by aggregating ...

The performance of Dynamic Positron Emission Tomography (PET) is often degraded by high noise levels. A key challenge is the significant variability across scans, which makes fixed denoising models ...

Large Language Models (LLMs) have revolutionized many areas of natural language processing, but they still face critical limitations when dealing with up-to-date facts, domain-specific information, or ...

Now that Daredevil: Born Again is back in the MCU spotlight, fans are excited about who’s joining the party for Season 2 as Jessica Jones is officially back on the case. In a recent interview with ...

LangGraph Multi-Agent Swarm is a Python library designed to orchestrate multiple AI agents as a cohesive “swarm.” It builds on LangGraph, a framework for constructing robust, stateful agent workflows, ...

Directed graphs and their afferent/efferent capacities are produced by Markov modeling of the universal cover of undirected graphs simultaneously with the calculation of volume entropy. Using these ...