Picking a JavaScript framework in 2026 is not the casual decision it was a decade ago. The framework you choose today will ...

Abstract: Graph neural networks (GNNs) have received great attention due to their success in various graph-related learning tasks. Several GNN frameworks have then been developed for fast and easy ...

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...

JavaScript’s low bar to entry has resulted in one of the richest programming language ecosystems in the world. This month’s report celebrates the bounty, while also highlighting a recent example of ...

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 ...

Large Language Models (LLMs) have set new benchmarks in natural language processing, but their tendency for hallucination—generating inaccurate outputs—remains a critical issue for knowledge-intensive ...

In today’s rapidly evolving digital landscape, JavaScript has firmly established itself as a cornerstone of web development. With an expansive ecosystem of frameworks at developers’ disposal, ...

Abstract: In modern industrial systems, accurate fault identification is crucial for the early isolation of broken parts and for further system restoration. Furthermore, data-driven machine learning ...

A competency framework seems to me to be largely compatible with a @graph. I suppose we could assign a graph level URI, but it would likely just be /graphs/ -- unless you know of a reason not to do ...