Depending on the underlying graph, you also need to handle cycles intelligently. In social networks, mutual relationships are ...

Abstract: Graph Neural Networks (GNNs) have recently achieved remarkable success in various learning tasks involving graph-structured data. However, their application to multi-relational graph anomaly ...

Without data, enterprise AI isn't going to be successful. Getting all the data in one place and having the right type of data tools, including connections to different types of databases is a critical ...

If you are like us, you love data, especially when it is presented in an orderly and appealing manner – think elegant charts and graphs. Data imagery is so popular that there is even a subreddit ...

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 ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...

Rajiv Shesh is the Chief Revenue Officer at HCLSoftware where he leads revenue growth & customer advocacy for Products & Platforms division. What’s really powering AI? High-quality data—foundational ...

In the age when data is everything to a business, managers and analysts alike are looking to emerging forms of databases to paint a clear picture of how data is delivering to their businesses. The ...

This library is being created by me to attempt a library, similar to C++'s "Standard Template Library", however, making it generic by using void pointers and enumeration as a way to store any data ...