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 ...

These are my go-to libraries for Python data crunching.

Conclusions: This study represents a pioneering effort in using LLMs, particularly GPT-4.0, to construct a comprehensive sepsis knowledge graph. The innovative application of prompt engineering, ...

Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.

Qualcomm confirmed a $3.92 billion all-stock deal to buy AI software startup Modular, paired with a Meta Platforms CPU ...

Abstract: Identifying drug-target interactions (DTI) is crucial in drug discovery and repurposing, and in silico techniques for DTI predictions are becoming increasingly important for reducing time ...

Attackers are actively exploiting path traversal and SQL injection in Langflow, LangGraph, and LangChain — below where your security tools look.

Nick Ewen is TPG's editor-in-chief and helps readers leverage credit cards (he has more than 25 of them) and loyalty programs to travel more for less. He's been at TPG for over 11 years. The cards we ...

Abstract: Deep-learning-based data-driven forecasting methods have achieved impressive results for traffic forecasting. Specifically, spatiotemporal graph neural networks have emerged as a promising ...