Support our Mission. We independently test each product we recommend. When you buy through our links, we may earn a commission. One of the areas where amateur golfers often struggle with distance ...

Support our Mission. We independently test each product we recommend. When you buy through our links, we may earn a commission. Dialing in your wedge distances is one of the most important data points ...

Abstract: In this paper, a Mahalanobis Distance-based Graph Attention Network for graph classification, is proposed. In contrast to traditional Graph Attention Networks, the proposed approach learns ...

Federated learning is a classic of privacy-preserving learning, which enables collaborative learning without sharing data. Structured data has become the mainstream of current applications, where ...

This magnetoencephalography study reports important new findings regarding the nature of memory reactivation during cued recall. It replicates previous work showing that such reactivation can be ...

Graph Neural Networks GNNs are advanced tools for graph classification, leveraging neighborhood aggregation to update node representations iteratively. This process captures local and global graph ...

Data augmentation (DA) has recently seen increased interest in graph mining and graph machine learning (ML) owing to its ability to create additional training data and improving resulting trained ...

Notes: Personally, these are the papers that have a very clear presentation to formulate and solve a problem / to construct a system.