Abstract: Recently, topological graphs based on structural or functional connectivity of brain network have been utilized to construct graph neural networks (GNN) for Electroencephalogram (EEG) ...

This important study combines optogenetic manipulations and wide-field imaging to show that the retrosplenial cortex controls behavioral responses to whisker deflection in a context-dependent manner.

Many local stories that could be harmful to Democrat politicians don’t become national TV stories for an obvious reason. In the case of the massive welfare fraud committed by Somalis in Minnesota ...

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The interaction between circular RNAs (circRNAs) and RNA-binding proteins (RBPs) plays ...

Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...

Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...

Abstract: Accurate prediction of regional power generation in renewable energy systems is crucial for grid dispatch optimization. However, photovoltaic power generation is subject to the influence of ...