A New Era in Skill Analytics Shekhar Agrawal, along with co-author Rahul Vats, introduces a groundbreaking innovation in ...

which make it difficult to generate effective graph embeddings directly by aggregating dynamic node embeddings. In this study, we propose a novel temporal attention network for learning graph-level ...

While Graph Convolutional Networks (GCNs) have significantly improved sleep staging accuracy by effectively processing complex data, current GCN-based methods often require a large number of signal ...

STGNNs is a Python-based implementation of Spatio-Temporal Graph Neural Networks designed for analyzing and predicting climate data. This model combines Graph Convolutional Networks (GCN) and advanced ...

You can learn a lot from a little slime mold. For Nate Cira, assistant professor of biomedical engineering in Cornell ...

The human brain continuously processes the wide range of information it acquires from the outside world. Over time, this ...

What do you wonder? By The Learning Network A new collection of graphs, maps and charts organized by topic and type from our “What’s Going On in This Graph?” feature. By The Learning ...

This valuable study provides new insights into the synchronization of ripple oscillations in the hippocampus, both within and across hemispheres. Using carefully designed statistical methods, it ...