Scientists tracking nearly 85,000 Americans for almost two decades say that as little as 15 minutes of brisk walking each day ...

We apply random walk node embedding with negative sampling and a gradient descent algorithm for graph-structural feature extraction. Our tabular dataset includes features and ground truth labels based ...

GAT-RWOS is a graph-based oversampling method that combines Graph Attention Networks (GATs) with random walk-based oversampling to address the class imbalance problem. By utilizing GAT's attention ...

Cousins referenced an old Bankroll Fresh song during a press conference.

The random walk theory suggests that asset prices, including in the cryptocurrency market, move randomly and unpredictably.

Recently graph auto-encoders have received increasingly widespread attention as one of the important models in the field of deep learning. Existing graph auto-encoder models only use graph ...

In our study, we adopted four types of prevailing graph embedding algorithms to obtain low-dimensional dense vectors of graph data: DeepWalk and Struc2Vec (based on random walk), SDNE (based on ...