India needs systems thinking in its curriculum to train doctors to grow beyond their medical roles and expertise ...

Abstract: Many graph-based algorithms in high performance computing (HPC) use approximate solutions due to having algorithms that are computationally expensive or serial in nature. Neural acceleration ...

AI is already rapidly redefining how we discover and design biologics, and as CTO at Cytiva, I’ve had the privilege of ...

Achieving a high OEE score has been elusive in the past as processors grapple with where to begin in troubleshooting OEE ...

Abstract: In the practical use of graph databases, storing graphs separately enhances maintainability, while integrating them into a unified graph facilitates advanced analytics. To address these dual ...

Thanks to the original implementations KAN (https://github.com/KindXiaoming/pykan) and FourierKAN (https://github.com/GistNoesis/FourierKAN), you guys are amazing ...

This code was tested with PyTorch 2.0.1, cuda 11.8 and torch_geometrics 2.3.1. Note that ${PROJECT_DIR} refers to this directory. The following section outlines the graph-to-graph transformation ...

In this study, we developed a dataset of behaviors associated with lameness in dairy cows. The data collection utilized IoT collars that were placed around the necks of 10 dairy cows. This publicly ...

The 2020 Nobel Prize in Chemistry was awarded for the development of CRISPR/Cas9, a method also known as "gene scissors," ...

1. Achievements and Challenges Coexist: The Dual Landscape of University Achievement Transformation ...

The banking industry, as the lifeblood of the modern economy, is actively embracing evolution as a "technology pioneer," ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...